Pandas is a fundamental library in Python for data manipulation and analysis, which provides rich functionalities and methods that enable data professionals to process and analyze large datasets. There are some advanced functions in Pandas that you should know for…
User profiling refers to creating detailed profiles that represent the behaviours and preferences of users, and segmentation divides the user base into distinct groups with common characteristics, making it easier to target specific segments with personalized marketing, products, or services.…
Creating a portfolio is a crucial step for a career in Data Science to showcase skills, projects, and experiences to potential employers or collaborators. If you want to know about some platforms you can use to showcase your Data Science…
The assumptions of Machine Learning algorithms are foundational principles that guide the algorithm’s design and application. There are some assumptions of Machine Learning algorithms that are commonly asked in interviews to test if you will be able to select the…
PySpark is the Python API for Apache Spark, an open-source, distributed computing system that offers an interface for programming entire clusters with implicit data parallelism and fault tolerance. PySpark brings the power of Spark to Python developers, allowing them to…
The comparison of multiple Machine Learning models refers to training, evaluating, and analyzing the performance of different algorithms on the same dataset to identify which model performs best for a specific predictive task. So, if you want to learn how…
Visualizing data effectively is crucial for analysis and communication. There are some data visualization rules that you should always follow to ensure your data visualizations are accurate and informative. So, if you want to know the essential data visualization rules…
One of the best ways to improve your Data Science skills is to work on real-world problems. Working on real-world problems helps you understand how to solve a Data Science problem from a particular domain or a particular type of…
SQL is one of the most valuable tools for working with data. There are some advanced SQL queries you don’t learn while learning the fundamentals of SQL, but are helpful in your job while analyzing data. So, if you want…
Food Delivery Cost and Profitability Analysis is a comprehensive evaluation aimed at understanding and optimizing the financial dynamics of a food delivery operation. The goal is to identify areas where the service can reduce costs, increase revenue, and implement pricing…
Learning Data Science is a journey that involves acquiring a broad set of skills, ranging from understanding the fundamentals of SQL and statistics to gaining hands-on experience with machine learning algorithms and practical implementation by working on projects. So, if…
Time Series data is a series of data points indexed in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time, making it a sequence of discrete-time data. It is widely used…
Learning Microsoft Excel is an unsaid rule for any Data Science job. It is a powerful tool that can perform simple to complex data manipulations, analysis, and visualization. So, if you want to know the essential Excel Formulas that you…
A Fashion Recommendation System using Image Features leverages computer vision and machine learning techniques to analyze fashion items’ visual aspects (like colour, texture, and style) and recommend similar or complementary products to users. So, if you want to learn how…
Geospatial Analysis refers to the process of analyzing and interpreting data that is associated with specific geographic locations. It consists of a wide range of techniques and tools designed to understand patterns, relationships, and trends across spatial dimensions. The outcomes…
Interviewing for a data science position typically involves several rounds to thoroughly evaluate a candidate’s skills and suitability for the role. Although the process of Data Science interviews can differ from country to country, there is a general process followed…
ANOVA, which stands for Analysis of Variance, is a statistical method used to analyze differences among group means and their associated procedures. It’s an essential tool in Data Science, particularly when comparing three or more groups for statistical significance. So,…
Metro Network Analysis involves examining the network of metro systems to understand their structure, efficiency, and effectiveness. It typically includes analyzing routes, stations, traffic, connectivity, and other operational aspects. So, if you want to learn how to analyze the metro…
Clustering analysis is a Machine Learning technique used to group a set of objects in a way that the data points in the same group (called a cluster) are more similar to each other than to the ones in other…
In Data Science, understanding different types of data distributions and their spread is crucial, as they provide insights into the nature of the data, its behaviour, and any underlying patterns. So, if you want to know about the types of…
Statistical equations are mathematical expressions that describe relationships, summarize data, or allow inferences and predictions. Some statistical equations form the backbone of many Data Science techniques. So, if you want to know the statistical equations you should learn as a…
A Text Generation Model is a type of Natural Language Processing (NLP) model that automatically generates human-like text. It can produce coherent and contextually relevant text based on the input text. So, if you want to learn how to build…
Many beginners in Data Science often get confused about how to choose data visualization graphs to visualize the data they are working on. Choosing the right data visualization graph depends on the nature of your data and the specific insights…
Becoming a successful data professional isn’t just about mastering technical skills. It’s more about developing the mindset of an analyst by being curious and systematic in your approach while solving any data science problem. Start thinking like an analyst to…
Probability provides the theoretical foundation needed to make statistical inferences, while statistics applies those theories to analyze and make sense of real-world data. Understanding probability and statistics is crucial for learning data science as these concepts form the backbone of…
Quantitative Analysis in the stock market involves the use of mathematical and statistical techniques to understand, predict, and make decisions about financial investments. If you want to learn how to perform Quantitative Analysis on stock market data, this article is…
Today, your education background doesn’t restrict you enough to get a career in your desired field. When it comes to Data Science, different educational backgrounds offer unique perspectives and skill sets that can be valuable in various aspects of data…
According to an IBM report, the worldwide average cost of a data breach in the previous year was $4.45 million which is a 15% increase in the last three years. Hence, it becomes imperative for organizations to protect these priceless…
A day in the life of a Data Scientist can vary significantly depending on the organization, the specific industry, and the projects they are working on. However, there are common elements that many Data Scientists experience in their daily work.…
In any real-world data collection, missing values can occur due to various reasons like errors in data entry, non-response in surveys, equipment malfunctions, or data corruption. Missing value imputation refers to replacing missing data with substituted values in a dataset.…
Car insurance modelling refers to the use of statistical and mathematical models to accurately predict events such as the frequency of claims, the severity of claims, or the total cost associated with claims, which in turn helps in pricing insurance…
Project-based interview questions focus on the projects you’ve previously worked on, often those listed on your resume as personal projects or the projects you have worked on in your previous job. Such questions can help interviewers to dive deep into…
Learning Python for Data Science is an essential step for anyone looking to enter the field, given Python’s status as one of the most popular programming languages for data analysis and machine learning. So, if you want to know how…
In Machine Learning, Classification tasks involve predicting categorical labels for input data, and having robust evaluation metrics that capture the nuances of these predictions is crucial. If you want to know how to evaluate the performance of Classification models, this…
An analytics dashboard is a data visualization tool that aggregates, displays, and analyzes key performance indicators (KPIs), metrics, and other key data points related to a business, department, or specific process. If you want to learn how to build an…
Business forecasting is the process of making predictions about future business events and performance based on historical data, statistical models, and business intelligence. If you are aiming for the roles of a Business Analyst, a Data Analyst, or a Data…
The impact of AI technologies like ChatGPT on job markets is a topic of much debate and discussion. We cannot run away from the fact that every decade brings new technologies, and we see a huge change in the job…
End-to-end Machine Learning Projects refer to comprehensive projects that encompass the entire lifecycle of a machine learning system, from the initial problem definition to the final deployment and ongoing maintenance. Building end-to-end projects will help you learn and go through…
Whether you’re a fresher or a working professional, preparing for a Data Science interview involves a series of steps to ensure you’re well-equipped to showcase your skills and knowledge. If you want to know how to prepare for Data Science…
Time series data is a sequence of data points collected or recorded at regular time intervals. Some common examples of time series include daily stock prices, monthly weather data, and yearly sales figures. If you want to learn how to…
An End-to-End Machine Learning Model is a comprehensive system that contains all the stages of a machine learning project, from data collection and preprocessing to model development, deployment, and ongoing maintenance. If you want to learn how to build an…
The ICC Men’s World Cup 2023 went beyond being a cricket tournament; it showcased the interplay between athletic prowess and technological innovation. This event’s utilization of data science marked a milestone emphasizing the harmonious blend of traditional sports strategies with…
Regression Analysis is a statistical method used in Machine Learning to understand and model the relationship between a dependent variable (also known as the target or response variable) and one or more independent variables (also known as predictor or explanatory…
The use of Data Science in the industry is to solve business problems. Companies are investing heavily to collect as much data as they can. This helps them in using data to build data-driven products. If you want to understand…
Aggregating and grouping are fundamental techniques in Data Science, often used to summarize or transform data for analysis. These techniques are essential when dealing with large datasets, as they help understand patterns and trends within the data. So, if you…
Real Estate Price Prediction is the process of estimating or forecasting the future prices of real estate properties, such as houses, apartments, or commercial buildings. The goal is to provide accurate property rates to buyers, sellers, investors, and real estate…
Text analysis, also known as text mining, focuses on extracting meaningful information and insights from structured and unstructured text data. It is crucial in various domains, including marketing, customer service, social media monitoring, content recommendation, and fraud detection. So, if…
WhatsApp’s core service, which includes text messaging, voice calls, and video calls, is free for individual users. However, it charges businesses to use its WhatsApp Business API, where WhatsApp uses various data-driven techniques to help businesses interact with customers at…
NumPy is the backbone of numerical computing in Python and is preferred in Data Science due to its efficiency, versatility, and extensive mathematical capabilities. If you want to know how to use NumPy for numerical computations, this article is for…
App Reviews Sentiment Analysis means evaluating and understanding the sentiments expressed in user reviews of mobile applications (apps). It involves using data analysis techniques to determine whether the sentiments in these reviews are positive, negative, or neutral. If you want…
Hey there! Let’s chat about something that’s really shaking things up in healthcare: machine learning (ML). Think of it as a super-smart computer that’s learning how to help doctors diagnose and treat us better. It’s like having a brainy sidekick…
Marketing is a fundamental business activity aimed to promote and sell products or services to customers. The primary goal of marketing is to understand customer needs and preferences, create products or services that meet those needs, and effectively communicate their…
Merging of Datasets in Data Science is the process of combining multiple datasets into a single, unified dataset. It is done to create a more comprehensive and complete dataset for analysis. If you want to learn the techniques used for…
When preparing for Machine Learning interviews, it’s crucial to have a good understanding of performance evaluation metrics, as they are key to assessing and improving model performance. So, if you are looking for some challenging interview questions related to performance…
Cohort Analysis is a data analysis technique used to gain insights into the behaviour and characteristics of specific groups of users or customers over time. If you want to learn how to perform Cohort Analysis, this article is for you.…
Tableau is a powerful data visualization tool used by Data Science professionals to transform raw data into interactive and understandable visualizations. It allows users to connect to various data sources, create dynamic charts, graphs, maps, and dashboards, and share these…
Machine learning is an advanced technology that now has been used for developments of so many fields and industries. Aside from website and app building, some businesses have successfully implemented this technology to improve the quality of their products and…
Hypothesis testing is a statistical method used to make decisions about population parameters based on sample data. It involves formulating null and alternative hypotheses, collecting data, and using statistical tests to determine the validity of the null hypothesis. If you…
Data science broadly encompasses data analysis, machine learning, data engineering, and statistical modelling. The path you take can vary based on the role you’re aiming for, such as a Data Analyst, Data Scientist, Machine Learning Engineer, or Data Engineer. So,…
Search Queries Anomaly Detection means identifying queries that are outliers according to their performance metrics. It is valuable for businesses to spot potential issues or opportunities, such as unexpectedly high or low CTRs. If you want to learn how to…
Hypothesis testing is a statistical method used to make decisions about population parameters based on sample data. It involves formulating null and alternative hypotheses, collecting data, and using statistical tests to determine the validity of the null hypothesis. Hypothesis testing…
Hypothesis Testing is one of the most valuable concepts for Data Science professionals. Significance level (alpha) and p-values are fundamental concepts in hypothesis testing. The significance level determines the risk of Type I errors, while p-values quantify the strength of…
Data Transformation involves converting and modifying data from its original format into a more suitable format for analysis. It aims to enhance the quality, usability, and effectiveness of the data for various analytical tasks. If you want to learn how…
E-commerce, short for electronic commerce, refers to the buying and selling of goods and services over the Internet. In E-commerce, businesses set up online platforms (websites or mobile apps) to showcase their products or services. Customers browse through these platforms,…
SQL is one of the most valuable tools for data professionals. Data professionals use SQL queries to extract relevant data for analysis. If you want to build an SQL project for Data Science but don’t know how to get started,…
Data Manipulation means altering, transforming, or restructuring data to prepare it for analysis, reporting, or other data-related tasks. It is a fundamental step in data management and analysis, as raw data often needs to be cleaned, organized, and refined to…
Customer Behavior Analysis is a process that involves examining and understanding how customers interact with a business, product, or service. This analysis helps organizations make informed decisions, tailor their strategies, and enhance customer experiences. If you want to learn how…
In a Data Science interview, candidates are often assessed on their knowledge of statistics, as statistics is a fundamental component of data analysis and modelling. If you want to know what kind of interview questions based on statistics you can…
Data Visualization is the graphical representation of data to help individuals, including Data Scientists and decision-makers, comprehend, analyze, and draw insights from complex datasets. It involves using various visual elements such as charts, graphs, plots, and maps to present data…
In the Finance domain, there are various Data Science jobs for leveraging data-driven insights to make informed financial decisions, manage risks, detect fraud, and optimize investment strategies. If you are interested in the Finance domain and want to know the…
A Book Recommendation System is a data-driven application designed to suggest books to users based on their preferences, reading history, and behaviour. It employs various data science and machine learning techniques to provide personalized book recommendations, enhancing the reading experience…
The retail domain refers to the sector of the economy that involves the sale of goods and services to consumers for their personal or household use. Retailers purchase products from manufacturers or wholesalers and then sell them to individual consumers…
Scikit-learn is a powerful library that provides a wide range of tools for data preprocessing and machine learning. It is built on top of other popular Python libraries like NumPy, SciPy, and Matplotlib, making it an integral part of the…
Ads CTR Analysis stands for Click-Through Rate Analysis for advertisements. Ads CTR Analysis is the process of examining the effectiveness of online advertisements by measuring the rate at which users click on an ad’s link to reach the advertiser’s website.…
Data analysis is the systematic process of inspecting, cleaning, transforming, and interpreting raw data to uncover meaningful patterns, trends, and insights. If you are looking for a job as a Data Analyst, you need to have some Data Analysis projects…
Time Series Forecasting is a statistical technique used to make predictions based on historical time-ordered data points. It’s valuable when dealing with data that changes over time, such as stock prices, sales figures, weather data, or economic indicators. ARIMA and…
There are various Data Science roles in the industry. Each role requires you to be an expert in some specific skills to get your first Data Science job. If you want to know what skills you should have for your…
Market Basket Analysis is a data-driven technique used to uncover patterns and relationships within large transactional datasets, particularly in retail and e-commerce. It helps businesses understand which products or items are often purchased together, providing insights for optimizing product placement,…
Deep Learning is a subset of Machine Learning that leverages deep neural networks to learn and represent complex patterns and features from data. If you are looking for a job specifically focused on Machine Learning, you should have at least…
Regression metrics are quantitative measures used to evaluate the performance of regression models. They provide information about how well a regression model fits the data and how accurately it predicts the outcome variable. If you want to learn how to…
SQL is a language that allows users to communicate with relational databases, which are structured storage systems designed to organize and store data in tables. These tables consist of rows and columns, much like a spreadsheet. SQL provides a standardized…
Stock Market Comparison Analysis is the process of evaluating and comparing the performance of multiple stocks or financial instruments within the stock market. It aims to provide insights into how different stocks have performed relative to each other and the…
Neural network architectures refer to the structural and organizational designs of artificial neural networks (ANNs). These architectures determine how the network is organized, including the number of layers, the number of neurons in each layer, the connections between neurons, and…
Data Resampling is a technique used in Data Science to adjust the size or distribution of a dataset. It involves modifying the existing dataset by either increasing or decreasing the number of data points. If you want to learn how…
Data Science means using data and computer science to solve business problems. There are various problems in Data Science that a Data professional deals with daily. If you want to know about the types of problems we deal with in…
Text Analysis, also known as Text Mining or Natural Language Processing (NLP), is a technique used to extract meaningful information and insights from unstructured text data, including documents, emails, social media posts, customer reviews, and more. If you want to…
Machine Learning means using data and algorithms to build intelligent systems. There are various Machine Learning algorithms used for training models that help in solving problems and building intelligent systems. While learning Machine Learning, many people are often confused about…
In Machine Learning, Feature Selection is the process of choosing a subset of relevant and significant features (variables or attributes) from features available in a dataset. The goal of selecting features is to improve the performance of a Machine Learning…
Data Visualization is a critical aspect of data science and analytics. It refers to presenting data in graphical or visual formats, such as charts, graphs, and maps, to help people understand the patterns, trends, and insights hidden within large and…
Customer Acquisition Cost (CAC) Analysis is a critical aspect of business strategy where Data Science plays a vital role. CAC refers to the cost a company incurs to acquire a new customer. Understanding and optimizing this cost is crucial for…
“Machine Learning Algorithms: Handbook” is a book based on a step by step guide to all Machine Learning algorithms with implementation using Python. In this article, I’ll give you a complete overview of the book so that you can understand…
Many people find solving a Data Science problem difficult even after mastering Machine Learning algorithms. The problem is that they focus more on algorithms than skills and the mindset of working with data. Data Science is not all about mastering…
Data manipulation is a fundamental process in data science that involves making changes, transformations, or adjustments to raw data to prepare it for analysis. This process is critical because real-world data is often messy, incomplete, or in a format that…
Cloud platforms, also known as cloud computing platforms, are comprehensive services provided by technology companies like Amazon, Microsoft, Google, and IBM, among others. These platforms offer a wide range of computing resources, including servers, storage, databases, networking, analytics, Machine Learning,…
Air quality index (AQI) analysis is a crucial aspect of environmental data science that involves monitoring and analyzing air quality in a specific location. It aims to provide a numerical value representative of overall air quality, essential for public health…
Domain knowledge refers to expertise and understanding of a specific field or subject matter. It encompasses the concepts, terminology, practices, and challenges associated with that domain. In Data Science, domain knowledge means a deep understanding of the industry, business, or…
Feature Engineering is a critical step in solving a Data Science problem that involves creating or selecting the most relevant and informative features (input variables) from raw data. These features are then used to train machine learning models, so the…
Data storytelling is a compelling way of communicating insights and information derived from data by constructing a narrative around it. It involves presenting data-driven findings in a clear, engaging, and relatable manner, similar to how a storyteller weaves a tale.…
Dating Recommendation refers to using data-driven techniques to provide personalized matchmaking suggestions to individuals seeking partners through online dating platforms. These recommendations are based on various factors and preferences, aiming to increase the likelihood of successful and compatible matches. If…
In Data Science interviews, technical questions are designed to assess your fundamentals of working with data and your understanding of using Data Science concepts in a given problem. If you want to understand what types of questions are asked in…
In Machine Learning, Ridge and Lasso Regression are regularization techniques used in linear regression to prevent overfitting and improve the model’s generalization to unseen data. They work by adding a penalty term to the linear regression loss function. If you…
Everyone has their own way of approaching a Data Science problem. If you are a beginner in Data Science, then your way of approaching the problem will develop over time. But there are some steps you should follow to start…
Fitness Watch Data Analysis involves analyzing the data collected by fitness wearables or smartwatches to gain insights into users’ health and activity patterns. These devices track metrics like steps taken, energy burned, walking speed, and more. So, if you want…
Questions like User Engagement Analysis are popular SQL questions in Data Science interviews. To solve this problem, you have to analyze user engagement to find the most engaging posts and users based on the given conditions. So, if you want…
Machine Learning means using data and algorithms to build intelligent systems. Machine Learning algorithms are computational procedures that enable machines to learn patterns and relationships from data without being explicitly programmed. These algorithms allow machines to make predictions, decisions, and…
Supply Chain involves coordination among various entities, such as suppliers, manufacturers, distributors, retailers, and customers, to optimize the process to minimize costs, enhance quality, and meet customer demands. If you are aiming for a Data Science job in retail, manufacturing, logistics,…
Demand Forecasting means estimating future customer demand for a product or service based on historical data and relevant factors. Inventory Optimization is the strategic management of inventory levels to ensure that the right amount of goods is available at the…
While learning Data Science, the decision between pursuing a degree or opting for courses and certifications can significantly impact your career trajectory. Your educational background plays a crucial role in determining the most suitable path for your journey in data…
In the Finance industry, various institutions and entities come together to facilitate financial transactions, manage risks, allocate resources, and make informed decisions, including commercial banks, investment banks, asset management firms, insurance companies, stock exchanges, regulatory bodies, and more. If you…
Python is a popular programming language for Data Analysis for several reasons. In the same way, Tableau and Power BI are powerful tools used in the industry for Data Analysis. It confuses a lot of people, especially beginners, why we…
Anomaly detection in transactions means identifying unusual or unexpected patterns within transactions or related activities. These patterns, known as anomalies or outliers, deviate significantly from the expected norm and could indicate irregular or fraudulent behaviour. If you want to learn…
Questions like Sales by Day of the Week Report are popular SQL questions in Data Science interviews. To solve this problem, you need to group the sales data by the day of the week, calculate the total sales amount for…
Marketing is a strategic and dynamic process to promote products or services to a target audience. It involves activities that create awareness, generate interest, and influence consumer behaviour. If you are aiming to work as a Data Science professional in…
Hyperparameter tuning is an essential process in Machine Learning that involves optimizing the settings that guide the training of a Machine Learning model. But these settings themselves are not learned from the data. These settings, called hyperparameters, play a vital…
A Web Data ETL (Extract, Transform, Load) pipeline is a systematic process used in data engineering to collect, transform, and load data from various sources on the internet into a structured and usable format for analysis and storage. So, if…
Questions like grouping sold products by date are popular SQL questions in Data Science interviews. In this problem, your task is to group the products sold on each date and calculate the total number of products sold on that date.…
In Data Science, time series refers to a sequence of data points recorded at specific time intervals. Time series data captures observations over time, where each data point corresponds to a particular moment or period. Time series analysis involves uncovering…
Data cleaning, also known as data cleansing or scrubbing, is a crucial step in data preparation and analysis. It refers to the systematic and meticulous identification, correction, and removal of errors, inconsistencies, and inaccuracies from data. The main objective of…
Forecasting the number of subscriptions Netflix will achieve in a time period is a vital business practice that enables them to plan, strategize, and make data-driven decisions. It enhances operational efficiency, financial planning, and content strategy, ultimately contributing to their…
In today’s competitive Data Science field, employers prefer candidates who can seamlessly bridge the gap between working with data and domain knowledge. By delving into projects that align with specific industries, you can demonstrate a deep understanding of the domain’s…
Questions like calculating the average selling price of various products are popular SQL questions in Data Science interviews. The average selling price is calculated by adding up all the selling prices of a specific product and dividing the total by…
Plotly is a powerful and versatile data visualization library used by Data Science professionals to create interactive and visually appealing plots, charts, and graphs. It enables users to represent complex datasets in a graphical form, making it easier to comprehend…
If you are looking for your first data science job, you need advanced and unique projects mentioned in your resume. A data science professional works with APIs to collect real-time data from company databases and third-party applications. Having at least…
A Music Recommendation System is an application of Data Science that aims to assist users in discovering new and relevant musical content based on their preferences and listening behaviour. Personalized music recommendations have become an essential tool in the digital…
Data analysis is the systematic process of inspecting, cleaning, transforming, and interpreting raw data to uncover meaningful patterns, trends, and insights. A data analyst is a Data Science professional skilled in working with data and equipped with the necessary tools…
Outliers are data points that deviate significantly from the rest of the data. These data points lie far away from the majority of the data points and can have a substantial impact on statistical analysis and modelling. If you want…
Recommendation systems are one of the popular applications of Data Science in every domain. The recommendation system of Amazon works by using both collaborative filtering and content-based filtering techniques. Amazon uses collaborative filtering to analyze user behaviour and recommend products…
Many web platforms and applications perform A/B testing to run experiments to find the best design, layout, or themes for their platform. Instead of relying on assumptions or hunches, applications and websites can test different design variations on real-time users…
Data Analysis means understanding the story behind the numbers. It is a systematic process of examining, cleaning, transforming, and interpreting raw data to uncover the story behind the data points. If you are learning Data Analysis, one of the best…
Neural Networks are a type of computational model inspired by the structure and functioning of a human brain. They are composed of interconnected nodes called neurons, organized into layers. Each neuron receives inputs, processes them, and produces an output that…
SQL is widely used in Data Science because it allows data science professionals to extract and manipulate data efficiently from databases. It is a powerful language for managing and analyzing structured data. If you are looking for some practical SQL…
Bank Account Summary is a popular SQL question in Data Science interviews. It involves generating a bank account summary in a specific format using SQL. So, if you want to know how to create a bank account summary, this article…
Matplotlib is a popular data visualization library for Python. It provides functions and tools enabling data scientists to create various plots and charts. Matplotlib allows data scientists to create high-quality visualizations that effectively communicate insights and patterns hidden within the…
Next Word Prediction means predicting the most likely word or phrase that will come next in a sentence or text. It is like having an inbuilt feature on an application that suggests the next word as you type or speak.…
A Machine Learning Engineer uses data and algorithms to build intelligent systems. If you are new to machine learning, you need to work on beginner-level machine learning projects to understand how to use machine learning algorithms on datasets to solve problems. If…
Python and R are preferred languages for data science due to their rich ecosystem of libraries, extensive community support, and powerful tools for statistical analysis, data manipulation, machine learning, and visualization. You can choose either Python or R for Data…
Calculating Ride Cancellation Rate is a popular SQL question in Data Science interviews. It involves analyzing the cancellation rate for ride requests, specifically from users who are not banned. So, if you want to know how to calculate the ride…
Pandas is a powerful open-source library in Python that provides high-performance data manipulation and analysis tools. Pandas enhances the productivity and efficiency of Data Science professionals by providing a comprehensive set of tools for data manipulation, analysis, and exploration. Its…
User Engagement Analysis is a data-driven approach to assess and understand user involvement, interaction, and satisfaction with a product, service, or platform. It involves analyzing various metrics and behavioural patterns to gain insights into user behaviour and preferences. It aids…
Data Engineering focuses on the foundational aspects of managing and processing data, providing the necessary infrastructure and pipelines to support Machine Learning and Analytics workflows. It ensures that data is reliable, accessible, and processed efficiently to enable data-driven decision-making and…
Market Analysis is a popular SQL question in Data Science interviews. It is often asked to understand your ability to manipulate and analyze data using SQL operations such as filtering, aggregating, sorting, and joining tables. So, if you want to…
NumPy, which stands for Numerical Python, is a powerful library in Python providing support for large, multi-dimensional arrays and matrices, along with a vast collection of mathematical functions to operate on these arrays. It serves as a fundamental building block…
Credit scoring and segmentation refer to the process of evaluating the creditworthiness of individuals or businesses and dividing them into distinct groups based on their credit profiles. It aims to assess the likelihood of borrowers repaying their debts and helps…
There are various Data Science tools used in the industry. The usage of different data science tools across companies and professions stems from the diverse nature of their data, objectives, and roles within the industry. Companies, ranging from small startups to large…
The problem of fixing names in a table is a popular SQL question in Data Science interviews. It involves using SQL queries to correct or modify names stored in a particular column. It helps the interviewer understand your data manipulation…
Market basket analysis is a Data Science concept that aims to understand customers’ buying habits to uncover associations and relationships between products. It focuses on analyzing the contents of customers’ shopping carts to identify frequently purchased items together. If you…
Dynamic Pricing is an application of data science that involves adjusting the prices of a product or service based on various factors in real time. It is used by companies to optimize revenue by setting flexible prices that respond to…
Mentioning projects in a resume is of the utmost importance as it allows potential employers to assess your practical skills and abilities. For Data Science jobs, it is essential to mention projects in your resume the right way, as it…
The problem of User Activity Analysis is a popular SQL question in Data Science interviews. It involves extracting and analyzing the user activity data within the designated timeframe of the number of given days. So, if you want to know…
RFM analysis stands for recency, frequency, and monetary value analysis. It is a data science concept used in marketing and customer relationship management. It involves analyzing customer behaviour and segmenting customers based on their transactional history, specifically focusing on three…
Data preprocessing is a critical step in data science tasks, ensuring that raw data is transformed into a clean, organized, and structured format suitable for analysis. A data preprocessing pipeline streamlines this complex process by automating a series of steps, enabling data…
Nike is an American multinational corporation engaged in the design, development, manufacture, marketing and worldwide sale of footwear, apparel, sports equipment, accessories and services. There are many ways how Nike uses Data Science to stay ahead of its competitors worldwide.…
The problem of product sales analysis is a popular SQL question in Data Science interviews. It involves analyzing product sales and identifying top-selling products based on total revenue. So, if you want to know how to solve this problem, this…
ARIMA (autoregressive integrated moving average) is a widely used statistical model for time series analysis and forecasting. It combines three key components: autoregression (AR), differentiation (I), and moving average (MA). In ARIMA models, the p, d, and q values are…
RFM Analysis is used to understand and segment customers based on their buying behaviour. RFM stands for recency, frequency, and monetary value, which are three key metrics that provide information about customer engagement, loyalty, and value to a business. So,…
Customer Segmentation is used to divide a company’s customer base into distinct groups based on common characteristics. It helps companies better understand their customers. If you want to understand Customer Segmentation and how Data Science professionals use this technique, this…
The problem of finding top-performing ads is a popular SQL question in Data Science interviews. It involves analyzing ad performance and identifying top-performing ads based on click-through rate (CTR). So, if you want to know how to solve this problem,…
Python has a remarkably clear and intuitive syntax, which emphasizes readability and thus reduces the burden of program maintenance. It is designed to be easy to understand and implement, making it ideal for beginners as well as Data professionals. So…
In Machine Learning, Scaling and Normalization are techniques used in data preprocessing to transform features or variables in a dataset. These techniques ensure that the data is in an appropriate range and distribution, which facilitates efficient training of Machine Learning…
A hybrid recommendation system is a recommendation technique that offers a complete and balanced approach by mixing two or more recommendation techniques. It aims to provide more accurate, diverse and personalized recommendations to users leveraging the strengths of different techniques…
Exploratory data analysis (EDA) is a Data Science concept where we analyze a dataset to discover patterns, trends, and relationships within the data. If you want to understand Exploratory Data Analysis, this article is for you. In this article, I will…
The problem of deleting duplicate emails is a popular SQL question in Data Science interviews. It involves identifying and removing duplicate records from a table that stores email addresses. So, if you want to know how to solve this problem,…
Exploratory data analysis (EDA) is a Data Science concept where we analyze a dataset to discover patterns, trends, and relationships within the data. It helps us better understand the information contained in the dataset and guides us in making informed…
The currency conversion rate or exchange rate is an important economic indicator affecting several sectors, such as import-export businesses, foreign investment and tourism. By analyzing past data and predicting future exchange rates, we can gain valuable insights to help stakeholders…
Lifetime value analysis calculates the expected value a customer/user will generate over the lifetime of their relationship with the company. So, if you want to know what Lifetime Value Analysis is and how a Data Science professional can help businesses…
The problem of employees earning more than their managers is a popular SQL question asked in Data Science interviews. It involves querying a database to identify employees earning a higher salary than their respective managers. So, if you want to…
H&M is a Sweden-based multinational clothing company that focuses on fast fashion clothing for men, women, teens and children. It is one of GenZ’s favourite brands worldwide. There are many ways in which H&M uses data science to keep its…
In today’s fast-paced e-commerce industry, fast and efficient order delivery is crucial to business success. To ensure seamless order fulfilment, businesses often partner with courier companies to ship their products to customers. However, managing the charges collected by these courier…
Demographic Analysis refers to analyzing data about a population, such as age, gender, income, education, and location, to better understand its characteristics, behaviour, and preferences. So, if you want to know what Demographic Analysis is and how a Data Science…
The problem of Customers Who Never Order is a common SQL question asked in Data Science interviews. It means querying a database to identify customers who have never placed an order. So, if you want to know how to solve…
A Business Analyst is a Data Science professional who uses the data generated by the business to analyze and forecast the performance of a business, design and manage the creation of new data products, and bridge the gap between business stakeholders and…
Loan Approval Prediction is one of the problems that Machine Learning has solved in fintech businesses like banks and financial institutions. Loan approval prediction means using credit history data of the loan applicants and algorithms to build an intelligent system…
Analyzing and Forecasting Time Series is a statistical technique used to analyze data points collected over time. It helps companies identify patterns and trends in the data, which can be used to make informed decisions about the future. So, if…
Finding uncommon words in two sentences is one of the problems in coding interviews. In this problem, you have to find all the words that appear only once in two given sentences. So, if you want to know how to…
In Machine Learning, Polynomial Regression is a regression algorithm used to model nonlinear relationships between input features and output labels. So, if you are new to Machine Learning and want to know how the Polynomial Regression algorithm works, this article…
Stock Market Performance Analysis involves calculating moving averages, measuring volatility, conducting correlation analysis and analyzing various aspects of the stock market to gain a deeper understanding of the factors that affect stock prices and the relationships between the stock prices…
Cohort Analysis is one of the real-time concepts that every Data Science professional should know. Cohort Analysis helps companies analyze and understand the behaviour of their customers or users over time. So, if you want to know what Cohort Analysis…
Transpose Matrix is one of the popular problems in coding interviews. This problem requires you to manipulate a matrix by flipping its rows and columns. So, if you want to know how to transpose a matrix, this article is for…
Support Vector Machine (SVM) is a popular supervised learning algorithm used for classification and regression problems in Machine Learning. The basic idea behind SVM is to find a decision boundary that separates data points of different classes with the maximum…
Customer lifetime value analysis is used to estimate the total value of customers to the business over the lifetime of their relationship. It helps businesses make data-driven decisions on how to allocate their resources and improve their customer relationships. So,…
A/B Testing is one of the real-world concepts you need to know as a Data Science professional. A/B Tests help businesses compare two different options or strategies, such as two different advertisements or website designs, to see which performs better…
Buddy Strings is a popular problem in coding interviews. In this problem, you need to check if it is possible to get two strings, different from exactly a swap of two letters. So, if you want to learn how to…
In Machine Learning, the Random Forest algorithm is an ensemble learning method for classification and regression tasks. It is composed of multiple decision trees, where each tree is built on a random subset of the input features and a random…
Not everyone is always available on social media all the time. Some people limit the use of social media during festive seasons, while some avoid social media during their examinations. So, as Content creators, we need to decide when to…
Content-based filtering and collaborative filtering are two common approaches used in recommendation systems. A Content-based recommendation system uses information about the recommended item, while a collaborative system uses user behaviour data. So, if you want to know how these approaches…
Binary Search is an algorithm used to find an element in a sorted array by repeatedly dividing the search interval in half. In coding interviews, there is always a question on any search algorithm. So, if you want to learn…
In Machine Learning, Decision Tree is an algorithm that works like a flowchart or tree structure to make decisions based on input data. It starts with a question or condition and then follows different branches based on the answers to…
Retail price optimization involves determining the optimal selling price for products or services to maximize revenue and profit. So, if you want to learn how to use machine learning for the retail price optimization task, this article is for you.…
As Data Science beginners, sometimes we need to find datasets to work on projects. And as Data Science professionals, we sometimes need to find synthetic data based on the problem we are working on. So, if you want to know…
Set Mismatch is a popular question in coding interviews. In this problem, you need to find two numbers in an array that are missing or duplicated. So, if you want to know how to solve this problem using Python, this…
In Machine Learning, Naive Bayes is an algorithm that uses probabilities to make predictions. It is used for classification problems, where the goal is to predict the class an input belongs to. So, if you are new to Machine Learning…
Store sales and profit analysis is the task of analyzing the performance of a retail store in terms of its sales and profits. It helps businesses identify areas for improvement and make data-driven decisions to optimize their operations, pricing, marketing,…
Data-driven business models are the types of business models in which data is used for overall business operations. Most big tech product companies you hear about today have data-driven business models. So, if you want to understand what Data-Driven business models…
User Funnel Analysis is a way to analyze the flow of users on a website or an application. It helps analyze the conversion rate on each page visited by the users. So, if you want to know how to analyze…
In Machine Learning, Logistic Regression is a statistical model used for binary classification problems. It is used to predict the probability of an outcome based on the input features. It uses a sigmoid function to map the input features to…
The supply Chain is the network of production and logistics involved in producing and delivering goods to customers. And Supply Chain Analysis means analyzing various components of a Supply Chain to understand how to improve the effectiveness of the Supply…
The first step to getting a job today is to create and upload your resume. The way you used to create a resume some years ago is very different from the way companies want you to. So, if you want…
Reorder routes to make all paths lead to the city zero is a popular question in coding interviews. In this problem, you need to reorder the connections between the cities so that all paths lead to the city labelled as…
In Machine Learning, Linear Regression Algorithm is a statistical technique for calculating the value of a dependent variable based on the value of an independent variable. The goal of linear regression is to find the best-fit line that describes the…
A chatbot is a computer program that understands the intent of your query to answer with a solution. Chatbots are the most popular applications of Natural Language Processing in the industry. So, if you want to build an end-to-end chatbot,…
Myntra is one of the fashion e-commerce platforms in India. It is known for its trending collection of clothing, footwear, and accessories. Myntra uses a lot of Data Science techniques that make it different from other e-commerce platforms. So, if…
Message Encryption means keeping the message secret. In simple words, Message Encryption means putting the message in a secret box that only the receiver can open. If you want to learn how to encrypt messages using Python, this article is…
You must have observed that some applications on your smartphone don’t charge anything but are still profitable. Most companies that are free for a user make money with the data of the users. So, if you want to know how…
Developing Data ETL pipelines is one of the most valuable skills for Data Engineers. Data ETL is a process where data is extracted from a place, then the data is transformed in some way, and then data is loaded into…
The price of a product is one of the most important decisions for every business. It means setting a price for a product or service that is affordable to the target consumer and helps the business remain profitable in the…
The problem of detecting capital is a popular question in coding interviews. A word is written in capital letters if all of its letters are uppercase or if only the first letter is uppercase and the rest are lowercase. In…
Data Preparation is one of the most valuable skills every Data Science professional should have. One challenging task in data preparation is filling in missing values and deciding what measure you should consider between mean, median, and mode to fill…
Accelerometer is a device used to measure the acceleration or vibrations of a motion. The data provided by an accelerometer is three-dimensional and can be used in data-driven applications for solving problems like fall detection and health monitoring. So, if…
Supply Chain Management is the management of the flow of goods from raw materials to the final products and ensuring the delivery of the demanded products at the right place and at the right time. There are many use cases…
The problem of checking perfect numbers is a popular coding interview question. A perfect number is a positive integer equal to the sum of its positive divisors, excluding the number itself. In this problem, you will be given an integer,…
There are many types of questions you are asked for a job interview to understand your behaviour, technical skills, domain expertise, and how you will use your skills in solving real-time business problems. If you are looking for some of…
Employee attrition analysis means analyzing the behaviour of the employees who left your organization and comparing them with the current employees in your organization. It helps in finding which employee may leave soon. So, if you want to learn how…
LinkedIn is a social media platform for working professionals. People use LinkedIn to know about industry trends, job seeking, and growing their professional network. So, if you want to know how LinkedIn uses Data Science, this article is for you.…
The problem of relative ranks is a popular coding interview question. Here you will be given an array of integers representing the scores of athletes, assuming that the athletes with the 1st rank will have the highest score, and you…
Customer Retention means keeping the existing customers loyal towards the business. Retaining customers helps businesses in repeat orders, profitability, and goodwill which attracts more new customers. Today businesses use your data to formulate strategies to retain you as a customer.…
Demand and Supply Analysis is a valuable concept used to analyze the relationship between the quantity demanded and the quantity supplied. If you want to learn about demand and supply analysis and how it helps businesses in the real world,…
Twitter is one of the popular social media applications today. It is known for expressing views in a short piece of text which makes it different from other social media applications. So, if you want to understand how Twitter uses…
The problem of License key formatting is a popular coding interview question. Here you will be given a license key, and you need to reformat the key such that each group contains the same characters except the first group. So,…
Advertising is a marketing strategy that businesses use to promote their products and services. Advertising is not a new concept, it has been used by businesses of all sizes to get more customers over the years. So, if you want…
A recession is an economic situation that arrives when the circulation of money in the economy is low for two consecutive quarters. When the circulation of money is low, it means people are not spending money in the market. When…
Mastercard Inc. is the second largest payment processing corporation worldwide. It offers a range of payment and financial services to businesses and customers worldwide. So, if you want to know how Mastercard uses Data Science for its business, this article…
The problem of constructing a rectangle is a popular coding interview question. Here you will be given the area of a rectangle, and you need to return the height and width of the rectangle to solve this problem. So if…
There is a huge competition in the Data Science field, making it hard to mention unique projects on your resume. An interviewer goes through hundreds of projects every day, so it’s essential to mention unique projects on your resume so…
Topic Modelling means assigning topic labels to a collection of text documents. The goal of topic modelling is to identify topics present in the text documents. So, if you want to learn how to perform topic modelling, this article is…
Samsung is a South Korean multinomial conglomerate. It is known for its midrange and flagship smartphone collection worldwide. There are many ways how Samsung uses Data Science and Machine Learning techniques in its technology and business. So, if you want…
The problem of max consecutive ones is a popular coding interview question. Here you will be given a binary array, and you need to return the maximum number of consecutive 1s in the array. So, if you want to know…
Your LinkedIn profile is like an online resume. Today, companies do have a look at your LinkedIn profile before hiring you, especially in the tech industry. So, if you want to know how to create a LinkedIn profile to get…
Text emotions classification is the problem of assigning emotion to a text by understanding the context and the emotion behind the text. One real-world example is the keyboard of an iPhone that recommends the most relevant emoji by understanding the…
There have been many innovations in the healthcare industry since the outbreak of covid in 2019. The use of data in the healthcare industry has helped healthcare professionals get more accurate information about the medical conditions of patients. In this…
The problem of hamming distance between two integers is a popular coding interview question. Here you will be given two integers, and you need to calculate the number of positions at which the corresponding bits of the integers are different. So, if…
A Data Engineer is a data professional who collects, transforms, and process data according to the need of the business. Data Engineering is one of the highest-paying jobs in Data Science. So, if you are looking for a roadmap to…
App user segmentation is the task of grouping users based on how they engage with the app. It helps find retained users, find the user segment for a marketing campaign, and solve many other business problems where you need to…
The problem of the Repeated Substring Pattern is a popular coding interview question. Here you will be given a string, and you need to check if the given string can be formed by repeating a substring of the string. So,…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. The role of a Data Analyst is one of the best jobs to start your journey as a Data Science…
Algorithmic Trading is the use of algorithms in the financial market to make trading decisions. JP Morgan Chase & Co. is one of the businesses that use Algorithmic Trading for investment decisions. So, if you want to learn how to…
Tata Consultancy Services is an Indian multinational corporation that provides IT, data processing and consulting services. TCS is one of the highly active recruiters in India for its IT and data processing services. So, if you want to know how…
The problem of assigning cookies is a popular coding interview question. Here you will be given a list of children with their greed factors and a list of cookies with their sizes. To solve this problem, you need to assign…
The decision Tree algorithm is a supervised Machine Learning algorithm used for both classification and regression problems. It is based on a sequential decision process. If you want to know everything about the Decision Tree algorithm, this article is for…
Ads Click Through Rate is the ratio of how many users clicked on your ad to how many users viewed your ad. For example, 5 out of 100 users click on the ad while watching a youtube video. So, in…
Dream11 is a fantasy sports platform where you can create a virtual team of real sports players and participate in fantasy games. Dream11 has many use cases of Data Science that make it different from all other fantasy gaming applications.…
Calculating the distance between two locations helps companies like Swiggy and Zomato calculate the delivery time for an order. If you want to learn how to calculate the distance between two locations by using their latitude and longitude points, this…
A box plot is a data visualization technique for analyzing the distribution and patterns of numerical data points. Understanding data visualization graphs is not easy for everyone. So if you want to know how to analyze a box plot, this…
A career aspirations survey gathers information about the goals and aspirations of people in their careers. It includes questions based on long-term goals, preferred work environment, interests, and values. So, if you want to learn how to analyze the information…
JP Morgan Chase & Co. is an American multinational investment banking and financial services company. Like other successful financial services businesses, Data Science is one of the reasons behind the success of JP Morgan Chase. So, if you want to…
The problem of counting the number of segments in a string is a popular coding interview question. Here you will be given a string, and you have to count the number of non-space characters in the string. So, if you…
A scatter plot is a data visualization technique to analyze relationships between two variables and find outliers. Understanding data visualization graphs is not easy for everyone. So if you want to know how to analyze a scatter plot, this article…
Food Delivery services like Zomato and Swiggy need to show the accurate time it will take to deliver your order to keep transparency with their customers. These companies use Machine Learning algorithms to predict the food delivery time based on…
Zomato is an Indian restaurant aggregator and food delivery company. It is known for faster delivery of food from anywhere in your city. Like every successful business today, Data Science is one of the reasons behind the success of Zomato.…
The problem of finding the third maximum number is a popular coding interview question. Here you will be given an array, and you have to return the third largest number in the array as an output. So, if you want…
Getting a Data Science job is hard for freshers without any work experience. So what should you do as a fresher? As a fresher, you can focus on entry-level job roles in Data Science to get experience. In this article,…
The Social Progress Index (SPI) is a measure that gives an understanding of social progress globally. It helps in understanding how much countries care about the overall development of the citizens. If you want to know how to analyze the…
Nykaa is one of the popular e-commerce platforms in India. It is known for beauty, wellness, and fashion products. Like every successful business today, Data Science is one of the reasons behind the success of Nykaa. So, if you want…
The FizzBuzz problem is a popular coding interview question. Here you need to check if a number is divisible by 3 and 5 and return the output based on some conditions. If you want to know how to solve the…
As a Data Science beginner, you need to work on various projects to get your desired job. Working on projects is valuable because your projects are the highlights of your resume when you are a fresher. Once you get experienced,…
Recommendation Systems are one of the popular applications of Data Science for every e-commerce platform. When it comes to fashion, an e-commerce platform wants to recommend the most trending fashion to its users for higher sales and engagement. Myntra is…
Spotify is an audio streaming platform with over 456 million monthly active users. Spotify is one of the best examples of companies that use Data Science and Machine Learning techniques to provide its services. So, if you want to know…
The problem of finding the first unique character in a string is a popular coding interview question. Here you will be given a string, and you have to return the index of the first non-repeating character in the string as…
One of the reasons behind the success of many businesses is how they use the data generated by their business and customers in decision-making and improving their products and services. So, if you want to know how companies worldwide use…
A recommendation system is a popular application of Data Science that recommends personalized content based on the users’ interests. Almost all the popular websites you visit today use a recommendation system. As the name suggests, a job recommendation system is…
Paytm is a digital payments and financial services company. Just like other fintech companies, data is the ABC for Paytm. So, if you want to know how Paytm uses Data Science, this article is for you. In this article, I…
Validating perfect squares is a popular coding interview question. Here you will be given an integer, and you have to check if the integer is a perfect square. So, if you want to learn how to validate perfect squares, this…
In Machine Learning, we use data and algorithms to build intelligent systems. In the next ten years, you will explore many new high-paying jobs that require you to know about Machine Learning. So the time you will spend today learning…
Banks and credit card companies calculate your credit score to determine your creditworthiness. It helps banks and credit card companies immediately to issue loans to customers with good creditworthiness. Today banks and credit card companies use Machine Learning algorithms to…
Youtube is a popular social media platform where we can upload videos to educate or entertain an audience of every kind. There are many areas where Youtube uses Data Science for its business and to provide a better user experience.…
Counting Bits is a popular coding interview question. Here you will be given an integer, and you have to return an array of length (length of the integer + 1) by counting the number of 1’s in the binary representation…
Data Science is one of the highest-paying career options today. There are many jobs in the Data Science field you can prepare for as a fresher or an experienced professional. So, if you want to know about the highest-paying career…
Consumer Complaint Classification means classifying the nature of the complaint reported by the consumer. It is helpful for consumer care departments as they receive thousands of complaints daily, so classifying them helps identify complaints that need to be solved first…
Apple is one of the most loved tech brands worldwide. Most of the products of Apple are known for productivity, user experience, and privacy. There are many ways how Apple is using Data Science and Machine Learning in its products…
The problem of the power of three is a popular coding interview question. Here we need to check whether the input value is the power of three or not. So, if you want to know how to solve this problem…
A Business Analyst is a Data Science professional who analyzes and forecasts business trends, understands and analyzes business strategies, and performs budgeting and financial analysis of the business. If you are aiming for the role of a Business Analyst and…
Every sports event generates a lot of data which we can use to analyze the performance of players, teams, and many highlights of the game. As the ICC Men’s T20 world cup has just finished, it has generated a lot…
Netflix is a subscription-based streaming platform that allows users to watch movies and TV shows without advertisements. One of the reasons behind the popularity of Netflix is the way Data Science is used at Netflix to improve its services as…
Moving zeroes is one of the popular questions in coding interviews. Here we need to move all the 0’s in an array to the end of the array while keeping the order of non-zero elements the same. So, if you…
Data Science is one of the highest-paying career options today. But many freshers find it hard to get their first Data Science job. Companies need experience, freshers look for work to become experienced, and the loop continues. So how to…
A/B Testing means analyzing two marketing strategies to choose the best marketing strategy that can convert more traffic into sales (or more traffic into your desired goal) effectively and efficiently. A/B testing is one of the valuable concepts that every…
Like all other jobs, the salary of a Machine Learning Engineer depends on many factors like work experience, living standards in the country, and demand for Machine Learning Engineers in the country. Out of all factors, work experience is the most important…
Grammarly is one of the best examples of applications that use Machine Learning for their business. Grammarly helps write a text for any purpose and uses Machine Learning to make that text more readable and engaging. So, if you want…
Ugly numbers are the numbers whose prime factors are limited to 2, 3, and 5. Finding the Ugly number is a popular question in coding interviews. Here you need to check if a number is an ugly number or not.…
Data Science is one of the highest-paying career options today. Data Science is not like Engineering, where you need an engineering degree with a computer science background. Data Science is a skill that helps companies make decisions with data. So…
Twitter is one of the popular social media applications where people share what they feel in a limited number of words. Twitter is popular but not in the stock market. As Twitter is being delisted from the New York stock…
Like all other jobs, the salary of a Data Scientist also depends on many factors like work experience, living standards in the country, and the demand for Data Science professionals in the country. Out of all these factors, work experience…
Instagram is one of the most popular social media applications today. Just like every business today, there are many areas where Instagram uses Data Science. So, if you want to know how Instagram uses Data Science, this article is for…
The problem of adding digits is a popular coding interview question. Here we need to add all the digits of the integer till we get to a single-digit integer. So, if you want to know how to solve this problem using…
Data Science is one of the highest-paying career options today. There are many free and paid platforms today where you can learn everything about Data Science. So, if you are looking for the platforms you should follow to learn Data…
Salary differs according to the job profile of the person. But generally, it’s the working experience that determines the salary. Salary prediction is a popular problem among the Data Science community for complete beginners. So, if you are a beginner…
With the increase in competition in the computer science field, coding interviews are getting tougher. It is now hard for freshers to get their first job in their dream companies. Although there are many free resources on the internet, if you are…
Google is the most used search engine worldwide. One of the reasons behind the success of Google as a search engine is the way Google uses Data Science to improve its search results for every user. So, if you want…
The problem of Power of Two is a popular coding interview question. Here we need to check whether the input value is the power of two or not. So, if you want to know how to solve this problem using Python, this…
Screen Time Analysis lets you know how much time you spend on what kind of applications and websites using your device. And screen time analysis gives a visual report of the same. So, if you want to learn how to…
A time series data is a sequence of data collected over an interval of time. When we work on time series data to analyze and find patterns, it is known as Time Series Analysis and forecasting. So, if you are looking for…
Amazon is one of the largest e-commerce platforms today. One of the reasons behind the success of Amazon is the way Amazon uses Data Science for its business. So, if you want to know how Amazon uses Data Science, this article is for…
The duplicate values problem is a popular coding interview question. Here we need to check if any value appears at least twice in an array. So, if you want to know how to solve this problem using Python, this article…
Data Scientists and Data Analysts are Data Science professionals with some skills in common and different responsibilities. So, if you don’t know how a Data Scientist differs from a Data Analyst, this article is for you. In this article, I…
In Data Science, weather forecasting is an application of Time Series Forecasting where we use time-series data and algorithms to make forecasts for a given time. If you want to learn how to forecast the weather using your Data Science…
Kaggle is a Data Science community owned by Google. You will find thousands of datasets and case studies on Kaggle to improve your Data Science skills. So, if you are looking for some case studies to practice your Data Science…
Tinder is an online dating and geosocial platform. Many users find Tinder helpful for meeting new people for friendships and relationships. Just like every business today, Tinder also use Data Science for its business. So, if you want to know how Tinder uses…
The majority element problem is one of the popular coding interview questions. Here we need to find the element that appears more than the other element in an array. So, if you want to know how to solve this problem,…
Data Scientists and Data Engineers are Data Science professionals with some skills in common and different responsibilities. If you don’t know how a Data Scientist differs from a Data Engineer, this article is for you. In this article, I will…
Flipkart introduces a sale every year during the festive season in India. This sale is known as the Big Billion Days sale. The focus of the sale is on electronics of every kind, including flagship smartphones. So, if you want…
There are many tools Data Science professionals use daily to solve business problems with data. To become a Data Science professional, you need to learn all the necessary tools. So, if you want to know about the tools and software…
Uber is an American mobility-as-a-service provider that currently operates in 72 countries. Uber is also among the companies that use data and algorithms as a necessity for their business. So, if you want to know how Uber uses Data Science, this…
The excel sheet column title is one of the popular coding interview questions. Here we need to return the corresponding column title of an integer as displayed in an excel sheet. So, if you want to know how to solve…
Data Scientists and Machine Learning Engineers are Data Science professionals with different skillset and responsibilities. So, if you are confused about how a Data Scientist differs from a Machine Learning Engineer, this article is for you. In this article, I…
Credit card clustering is the task of grouping credit card holders based on their buying habits, credit limits, and many other financial factors. If you want to learn how to use clustering analysis to group credit card holders, this article…
In Machine Learning, we use data and algorithms to build intelligent systems. If you are preparing for a job based on Machine Learning and confused about what kind of projects you should work on to mention in your resume, this…
In Machine Learning, we use data and algorithms to build intelligent systems. It doesn’t matter if you want to become a Machine Learning Engineer, Data Scientist, or Data Analyst. If you want any job in the Data Science field, you need…
The Single Number problem is one of the popular coding interview questions. Here you will be given an array of integers where each item appears twice except for one that we need to find. So, if you want to know how…
Regression analysis is a machine learning technique used to predict continuous values. Once you have trained a regression model to predict Continuous values based on the problem you are solving, it is valuable to evaluate the model’s performance. So, if…
A diamond is one of the most expensive stones. The price of diamonds varies irrespective of the size because of the factors affecting the price of a diamond. So, if you want to learn how to use your Data Science…
Python is one of the most popular programming languages today. The popularity and beginner-friendly nature of Python’s syntax have made it accepted in almost every domain worldwide. To get your first job as a Python developer, you need to work…
Python is one of the most popular programming languages today. It is preferred by Data Science professionals and Web Developers worldwide. There are a lot of free and paid courses on the internet to learn Python. So, if you are…
Palindrome words are words that are read the same backward as forward. For example, mom, dad, and madam are palindrome words. Validating palindrome words is one of the popular coding interview questions. So, if you want to learn how to…
Data Science is the combination of data mining and computer science. As the use of data has increased in every domain, Data Science is one of the highest-paying career options today. If you want to learn Data Science and looking…
Apple iPhones are among the top-selling smartphones worldwide. There is huge competition among smartphone brands in India, where you can get the latest technology in a smartphone at half the price of an iPhone. Still, there are high sales of iPhones…
Instagram is one of the most popular social media apps today. It contains valuable features for both content creators and consumers. There are many areas where Instagram uses Data Science to make it more helpful to its users. So, if…
Data Science is one of the highest-paid career options today. If you want to learn Data Science, you don’t need to spend a lot as there are so many free resources on the internet to learn Data Science. So, if…
Finding the best time to buy and sell stocks is one of the popular coding interview questions. Here we need to return the maximum profit we can achieve from buying and selling a stock. So, if you want to learn…
A recommendation system is a popular application of Data Science. Almost all the popular websites you visit use recommendation systems. As the name suggests, a news recommendation system is an application that recommends news articles based on the news a user is…
Business Forecasting is one of the popular applications of Data Science. In Business Forecasting, we use the data generated by the business to forecast the future sales, expenditure, or revenue of the company. If you are looking for some project…
In Machine Learning, we use data and algorithms to build intelligent systems. It doesn’t matter if you want to become a Machine Learning Engineer, Data Scientist, or Data Analyst. If you want any job in the Data Science field, you…
Pascal’s Triangle is one of the popular coding interview questions. It is asked in the coding interviews by FAANG companies many times. In Pascal’s Triangle problem, we need to return the number of rows of a Pascal’s Triangle. So, if…
Data Analysts and Business Analysts are Data Science professionals with different skillset and responsibilities. Both these professions are not completely different. So, if you are confused about how Business Analysts and Data Analysts are different, this article is for you.…
Business Forecasting is one of the applications of Time Series Forecasting. In Business Forecasting, we aim to forecast future sales, expenditure, or revenue by using the historical Time Series data generated by the business. So, if you want to learn…
A Business Analyst is a Data Science professional who uses the data generated by the business to analyze and forecast the performance of a business. If you are aiming for the role of a Business Analyst and want to know what…
MySQL is an open-source relational database management system. Knowing MySQL will always help you in your career in any field of computer science. So, if you are a MacBook user and want to know how to install MySQL on your…
Climbing Stairs is one of the popular coding interview questions. It is asked in the coding interviews by FAANG companies many times. In the climbing stairs problem, you need to count the number of distinct ways to climb to the…
Python is one of the most popular programming languages today. It is preferred by Data Science professionals and Web Developers worldwide. If you are someone who has just started learning Python or looking for a step-by-step roadmap to learn Python,…
Natural Language Processing (NLP) is a subset of Artificial Intelligence where we aim to train computers to understand human languages. Some real-world applications of NLP are chatbots, Siri, and Google Translator. While working on any problem based on NLP, we…
Working on Data Science projects is one of the best ways to improve your Data Science skills. It not only boosts your skills but also strengthens your resume. So, if you are a Data Science beginner and want to know how to…
A Data Engineer is a Data Science professional who collects, transforms, and process data according to the need of the business. Data Engineering is one of the most in-demand Data Science jobs. So, if you are aiming for the position…
Finding the square root of a number is asked in the coding interviews by FAANG companies many times. A square root is a number that produces the specified value when multiplied by itself. For example, 5×5 gives 25, so the square root…
Python has a vast collection of built-in modules we don’t learn while learning the fundamentals of Python. As a beginner, you don’t need to learn all the modules to become an expert in Python. So, if you want to know…
Password Strength Checker is an application that checks how strong a password is. Some popular password strength meters use machine learning algorithms to predict the strength of your password. So, if you want to learn how to use machine learning…
Apple is one of the most loved smartphone brands worldwide. Apple’s iPhone is known for productivity, user experience, and privacy. There are a lot of areas where Apple uses Machine Learning to improve the overall user experience of an iPhone.…
Data Science is a combination of data mining and computer science. It is one of the most in-demand career options in the industry. Still, many Data Science freshers struggle to get their first job as most companies look for experienced Data…
The Plus One problem is one of the popular coding interview questions. It is asked in the coding interviews by companies like FAANG many times. Here you need to increment the last digit of an array by one and return…
A Python Developer is one of the developers in the development team who works at the backend to create, design, debug and deploy applications using Python. If you are good at Python and looking for your first job as a…
The rent of a house depends on a lot of factors. With appropriate data and Machine Learning techniques, many real estate platforms find the housing options according to the customer’s budget. So, if you want to learn how to use…
Deep Learning is a subset of Machine Learning where we need a large amount of data to train powerful models capable of finding relationships in the data to solve complex problems. So, if you are looking for courses that will…
Statistics means collecting, organizing, analyzing, interpreting, and presenting data. Statistics is one of the most valuable concepts for Data Science. A person with statistical background is preferred for the role of a Data Science professional. So, if you are looking…
Removing duplicate values from a sorted array is one of the popular coding interview questions. It is asked in coding interviews by companies like FAANG many times. Here you need to return an array of unique values by removing all the…
In Machine Learning, the concept of model evaluation means determining the performance of a Machine Learning model. To evaluate the performance of a Machine Learning model, we need to use model evaluation metrics. So, if you want to learn classification…
In Machine Learning, we use data and algorithms to build intelligent systems. There are a lot of free resources on the internet you can follow to learn Machine Learning. But some people like to learn from courses to learn everything…
Social Media applications are those applications where you get a collection of features based on communication, interaction, content creation, and collaboration. Facebook, Instagram, Youtube, and Twitter are some of the popular social media applications today. Every social media application uses Data…
Merging two sorted lists is one of the popular problems in Leetcode. It is asked in coding interviews by companies like FAANG many times. Here you need to return a sorted list by merging two sorted lists. So, if you…
Spam comments detection means classifying comments as spam or not spam. YouTube is one of the platforms that uses Machine Learning to filter spam comments automatically to save its creators from spam comments. If you want to learn how to…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. Data Analysis is so popular that you can learn everything about it without spending any money. But some people like to…
E-commerce is nothing but the buying and selling of goods and services over the internet. Amazon is one of the most popular e-commerce platforms in the world. So, if you want to know how E-commerce platforms use Data Science, this…
Longest Common Prefix is one of the popular problems in Leetcode. It is asked in coding interviews by companies like FAANG many times. Here you need to return the longest common prefix among all the strings in an array of…
A recommendation system is one of the popular applications of Data Science. A restaurant recommendation system is an application that recommends similar restaurants to a customer according to the customer’s taste. If you want to learn how to build a…
Data Analysis means analyzing data to gather valuable insights that can be used in decision-making and solving various business problems. So, if you are looking for a step-by-step guide to learning Data Analysis, this article is for you. In this…
Astronomy is the study of everything we see with the naked eye or discover from the telescope, satellites and other instruments in the universe. The instruments used to study the universe collect data in many forms. Scientists use this data…
Two Sum is a popular problem in Leetcode. It is often asked in coding interviews from companies like FAANG. Here you need to return the indices of integers from an array whose addition equals the target value. So, if you…
A recommendation system is one of the popular applications of Data Science. A Book Recommendation system is an application used to recommend similar books to a user. If you want to learn how to build a book recommendation system, this…
While learning a new programming language, it is valuable to solve practice questions. When you solve questions, it develops problem-solving skills. If you are learning Python and have completed the fundamentals of Python, your next step should be to solve…
Fintech means using technology to provide financial services. There are a lot of Fintech companies we take any finance service from daily. Some worldwide known examples of Fintech companies are Mastercard, Visa, Stripe, and Paypal. Data is considered the ABCD…
Finding the missing number in an array is a popular coding interview question. According to LeetCode, this question is popular in the interviews of companies like Amazon, Adobe, Microsoft, LinkedIn, and many more. If you want to learn how to…
Stock Market Analysis means analyzing the current and historical trends in the stock market to make future buying and selling decisions. Stock market analysis is one of the best use cases of Data Science in finance. So, if you want…
A Data Analyst analyzes data to gather valuable insights that can be used for decision-making and solving various business problems. The job of a Data Analyst can be different in every organization and every domain. But there are some responsibilities…
The activities a business performs to promote its products or services among the target population is known as Marketing. There are a lot of problems where Data Science is used in the marketing domain. So, if you want to know…
Grouping elements of the same indices means grouping elements of two or more data structures according to their indices. It is a tricky problem for beginners and can be asked in any coding interview. If you want to learn more…
Netflix is a subscription-based streaming platform that allows users to watch movies and TV shows without advertisements. One of the reasons behind the popularity of Netflix is its recommendation system. Its recommendation system recommends movies and TV shows based on…
Data Analysis is the process of analyzing data to gather valuable insights that can be used for decision-making and solving various business problems. There are many tools that you can use for Data Analysis. In this article, I will take…
If you visit some of the LinkedIn profiles of Data Science professionals, you will notice that most of them don’t have a master’s or a bachelor’s degree in Data Science. Most of them have engineering or statistical background. They don’t…
The number guessing game is a popular game among programmers. In the number guessing game, the program selects a random number between two numbers, and the user guesses the correct number. If you want to learn how to create a…
Website Traffic Forecasting means forecasting traffic on a website during a particular period. It is one of the best use cases of Time Series Forecasting. If you want to learn how to forecast traffic on a website, this article is…
Data science is a combination of data mining and computer science. Data plays an important role in every data science task. As a data science professional, you need to know what kind of data you are working with to solve…
Time Series Forecasting is the process of analyzing and modeling time-series data. It helps in forecasting the future behaviour of the market, which is helpful in the decision-making for every business. Some of the applications of Time Series Forecasting are…
While working on a Data Science task, sometimes we have to deal with textual data. One of the problems beginners face while working on a textual dataset is counting the number of words in a piece of text. So if…
Time Series Forecasting means analyzing and modeling time-series data to make future decisions. Some of the applications of Time Series Forecasting are weather forecasting, sales forecasting, business forecasting, stock price forecasting, etc. The ARIMA model is a popular statistical technique…
As a beginner in the Python programming language, you must have heard that the applications of Python are Data Science, Machine Learning, Data Analysis, Web Development, Automation, and even Robotics. But what are the existing applications of Python in the…
Salary is one of the most valuable factors in choosing a career. No one would like to prepare for a job that doesn’t pay well. So, if you are preparing for the role of a Data Science professional and want…
Emojis are used to express our emotions while writing a message or any piece of text. If you want to learn how to display emojis in the output using the Python programming language, this article is for you. In this…
Instagram is one of the popular social media applications today. People use Instagram to share photos and videos. One of the reasons behind the popularity of Instagram is its recommendation system. It helps in grabbing the attention of the user…
Web Scraping means collecting data from a web page. It is one of the techniques used by Data Science professionals to create datasets. Python has a collection of useful libraries for web scraping. If you want to know about those…
Data science is one of the highest paying career options today. There are many jobs in this field, some of the most popular of which are Data Scientist, Data Analyst, Data Engineer, and Machine Learning Engineer. If you know you…
Seaborn is one of the best Python libraries for Data Visualization. It is built on top of Matplotlib. Unlike Matplotlib, Seaborn cannot be the only Data Visualization library in your skillset, but some visualizations look better and more understandable with…
There has been a high demand for online food orders after the introduction of Swiggy and Zomato in the market. Food delivery companies use your buying habits to make the delivery process faster. The food order prediction system is one…
The new MacBooks with the M1 processor provide so many specifications that are enough for every Data Science and Machine Learning professional. But if you have just purchased a MacBook, you have to create a virtual environment to prepare it…
Python is one of the best programming languages today. On macOS, Python is preinstalled and available to use. But people often find it hard to install the latest version of Python on macOS. So if you have just purchased a…
Correcting spellings in a piece of text is one of the handy features that can be used in any application where users write content. For example, if you want to create a notepad, it should have a feature to identify…
There is a lot of competition among the brands in the smartwatch industry. Smartwatches are preferred by people who like to take care of their fitness. Analyzing the data collected on your fitness is one of the use cases of…
If you are a beginner in Python, you must be using the IDLE code editor that comes with Python. There are many better code editors and tools you will need to use as a Python programmer. So, if you want…
Working on a data science project is one of the best ways of showing your skills in working with data. If you are a data science student, your university will ask you to submit a report on your data science project in…
Anagrams are words formed by rearranging the letters of another word, For example, car and arc, cat and act, etc. Grouping anagrams is one of the popular questions in coding interviews. So if you want to learn how to solve…
Sentiment analysis of reviews of a product or service helps businesses understand what their customers want from them. Analyzing the reviews is one of the primary use cases for sentiment analysis. If you’re looking for data science projects on sentiment…
Tinder is one of the most popular dating applications. It connects people having similar interests. To check whether Tinder helps people find partners, we can analyze the sentiments of people about Tinder. There are a lot of reviews on the…
TensorFlow is one of the most powerful frameworks for Machine Learning. It was created by Google and used by companies like Airbnb, Spotify, and Google. So if you are looking for the best resources to learn TensorFlow, this article is…
Python is one of the most valuable programming languages in the industry. It is preferred by data science professionals and web developers. If you are looking for a complete course to learn Python, this article is for you. This article…
Many computer science students look for programming project ideas in their final year. Your final year project should be on a real-time problem. So if you are a final year student and looking for some Python project ideas, this article…
MNIST Digits classification is one of the popular case studies in the data science community. It is based on the problem of Classification in Machine Learning. If you are a beginner in Machine Learning, you must try to solve this…
One of the tasks while solving a machine learning problem using Python is to convert a Pandas DataFrame to a NumPy array. A pandas DataFrame is a DataFrame object that we use to work with data, and a NumPy array…
Data Science is one of the highest-paid career options today. It is so popular that you can learn everything about data science without spending any money. But some people like to choose a paid course over free resources as we…
Rock Paper Scissors is a hand game usually played between two people. In this game, scissors can beat paper, paper can beat rock, and rock can beat scissors. If you want to learn how to create a rock paper scissors…
Data Analysis is the process of analyzing a large amount of data to find relationships between different features in the data. If you are a final year student of business analysis or data analysis and looking for some data analysis…
Analyzing a player’s performance is one of the use cases of Data Science in sports analytics. Virat Kohli is one of the most famous cricketers in the world. So it will be a great data science project if we analyze…
As a Data Science Professional, it is valuable to learn about using cloud computing platforms like Google Cloud Platform (GCP) or Amazon Web Services (AWS) for Data Science. So if you want to know how to learn Google Cloud Platform…
In Machine Learning, we use data and algorithms to build intelligent systems. If you are new to machine learning and looking for a certification or course to learn and get certified in machine learning, this article is for you. In…
Web scraping is one of the most valuable skills every coder should have. If you want to learn how to collect data from GitHub using web scraping techniques, this article is for you. In this article, I will take you…
Sports Analytics is the task of analyzing sports data. It includes player performance analysis, analysis of all game highlights, data storytelling and summary of a sports tournament, comparison of strengths and weaknesses of teams and players, etc. So, if you’re…
Every sporting event today generates a lot of data about the game, which is used to analyze the performance of players, teams, and every event of the game. So the use of data science is in every sport today. Currently,…
As a data science professional, it is important to learn how to use cloud computing platforms like Amazon Web Services or Google Cloud Platform for data science. So, if you want to know how to learn Amazon Web Services for…
As a beginner in data science, the choice of topics for data science projects depends on the ease of availability of datasets. Sometimes students think about unique topics, but they can’t find a dataset for their project. So if you…
Text generation involves generating text using machine learning techniques. The purpose of text generation is to automatically generate text that is indistinguishable from a text written by a human. If you want to learn how to generate text with Python,…
Data Science is one of the best career options in this data-driven world. There are a lot of technical skills required to work as a data science professional in any domain. If you are learning Data Science and are looking…
Student marks prediction is a popular data science case study based on the problem of regression. It is a good regression problem for data science beginners as it is easy to solve and understand. So if you want to learn…
Power BI is a data visualization tool from Microsoft. It lets us easily connect to data and visualize it to discover necessary insights. As a data science professional, you must know Power BI or Tableau. So, if you are looking…
Data analysis means working with data to gather the information which can be used for decision making and solving various business problems. There are many free resources on the internet for learning data analysis. But if you are looking for…
A list is a collection of items provided by the Python programming language, whereas a dictionary in Python is used to store data into key and value pairs. If you want to learn about converting two Python lists into a…
The use of data science is in all fields today. Economics is one of the fields in which we study the growth of a country by understanding the data on the economic factors of a Country. So, if you want…
The outbreak of Covid-19 resulted in a lot of restrictions which resulted in so many impacts on the global economy. Almost all the countries were impacted negatively by the rise in the cases of Covid-19. If you want to learn…
Tableau is one of the most popular data science tools used for data visualization and analysis. If you want to become a data scientist, you need to know how to use Tableau. So if you’re looking for some of the…
Python has been one of the best programming languages for a long time now. It is preferred by data science professionals and web developers around the world. Many companies need skilled Python developers. If you want to get a job…
Sometimes a Python developer needs to collect some text information from PDF files. So extracting text from a PDF is a problem you should know how to solve as a Python developer. If you want to learn how to extract…
In Machine Learning, we use data and algorithms to build intelligent systems. If you are new to machine learning, you need to work on beginner-level machine learning projects to understand how to use machine learning algorithms on datasets to solve…
TikTok is one of the most popular social media apps today. It is famous for its short videos. People often use this app to watch entertaining and funny videos. Despite its entertaining content, this application is not liked by everyone.…
Data Science certifications are all about certifying whether a person knows how to work with data or not. Although if you have a good list of projects in your portfolio, you don’t need any data science certification. Having a certification…
A Python developer can work as a web developer, API developer, data analyst, and sometimes a developer who writes reusable code for the complete team of developers. The role of a Python developer may differ from company to company, but…
A linear relationship is a statistical term that is nothing but the relationship between two variables. A linear relationship shows how well two variables x and y are related to each other. As a data science professional, you should know…
Many beginners in data science are often confused about what job role they should prepare for. People who are starting to learn data science have either an engineering background, a statistical background, or a non-computer background. Each person has their…
Clustering is a machine learning technique to group data points characterized by specific features. Clustering music genres is a task of grouping music based on the similarities in their audio characteristics. If you want to learn how to perform clustering…
Many data science beginners can solve any data science problem by following a tutorial, but they often struggle to solve a new data science problem. It’s not easy for beginners to start solving a problem when they see a new…
Natural language processing (NLP) is a subfield of artificial intelligence and computer science. NLP is the process of processing and analyzing natural language data to create intelligent applications that can understand human languages. Like machine learning, Python is also preferred…
Mean, Median and Mode are the fundamentals of statistics used in almost every domain where we deal with numbers. Python is one of the best programming languages for numerical calculations. So you should know how to calculate mean, median and…
SQL is one of the most important skills for data science professionals. Most data science beginners don’t focus on learning SQL as much as on learning Python. SQL is as important as Python for data science, especially if you’re looking…
Covid-19 is one of the deadliest viruses you’ve ever heard. Mutations in covid-19 make it either more deadly or more infectious. We have seen a lot of deaths from covid-19 while there is a higher wave of cases. We can…
Python is one of the best programming languages today. It is preferred by web developers and data science professionals around the world. When we learn a new programming language, it is important to work on some basic projects to improve…
In Python, Break and Continue are statements executed inside a loop. These statements either skip according to the conditions inside loops or terminate loops at a point. If you want to learn all about the Break and Continue expressions in…
Matplotlib is one of the most preferred Python libraries for data visualization. If you are learning data science, you must be aware of the kinds of data visualizations you need to work with. In this article, I will not focus…
Data Analysis is one of the best career options for someone who is not from a computer science background and still wants to build a career as a Data Science professional. As data analysis is a popular field today, you…
Instagram is one of the most popular social media applications today. People using Instagram professionally are using it for promoting their business, building a portfolio, blogging, and creating various kinds of content. As Instagram is a popular application used by…
Python is one of the most popular programming languages for a long time now. There are so many big tech companies that are using Python. It’s easy to learn and implement Python, that is why so many developers are choosing…
If you are a Data Science student, you must have found it hard to choose a topic for creating your first data science project as a beginner. Some universities give a list that you can choose from, while some universities…
A string is a sequence of characters enclosed in single or double-quotes. String inversion is one of the most common problems in computer science. Here we need to reverse the characters of a string. So, if you want to learn…
In machine learning, we use data and algorithms to build intelligent systems. Companies use machine learning to make their systems and applications smart enough to give a better user experience to the customers. As machine learning is a popular skill,…
Today is the 19th day of war between Russia and Ukraine. Many countries are supporting Ukraine by introducing economic sanctions on Russia. There are a lot of tweets about the Ukraine and Russia war where people tend to update about…
Data science is one of the highest-paying career options in this data-driven world. Every company now makes decisions based on the data generated by its business. A company, therefore, needs skilled data science professionals to turn raw data into actionable…
Machine Learning is a branch of Artificial Intelligence where we use data and algorithms to build intelligent systems. It is one of the highest-paid skills in the industry today. If you want to learn machine learning, you should know that…
Web Scraping is one of the skills that every data science professional should know. Sometimes the data we need is available on a website in the form of a table which cannot be downloaded directly from the website. To use…
As a beginner in data science, it’s hard to understand all the concepts you learn without implementing them on a dataset. Working on data science projects and case studies will help you improve your data science skills. If you’re struggling…
Breast cancer is one of the types of cancer that starts in the breast. It occurs in women, but men can get breast cancer too. It is the second leading cause of death in women. As the use of data…
YouTube is one of the platforms where millions of people can learn anything for free, as there are so many content creators on YouTube that create valuable content for its audience. So if you are learning data science and looking…
If you are new to machine learning, you have to choose a programming language to learn machine learning and implement it on data. Python is one of the most preferred programming languages for machine learning. So if you want to…
SequenceMatcher is a class in Python available in the difflib module, which provides functions for comparing sequences in two different pieces of text. So whenever you want to compare two text files, you can explore the difflib module in Python.…
Data Visualization is one of the most important skills that every data scientist should have. Data visualization helps in analyzing data by summarizing the data into graphs, which helps understand the story behind the numbers. There are so many tools…
Predicting the future sales of a product helps a business manage the manufacturing and advertising cost of the product. There are many more benefits of predicting the future sales of a product. So if you want to learn to predict…
You must have seen a lot of people in the data science community using Python often and promoting the use of Python for data science. So is it just their biases with Python or it is best for Data Science?…
Data Structures and Algorithms are the pillars of every coding interview. Most coders learn the essential data structures and algorithms but still fail to crack coding interviews. So what you should do is solve various problems based on data structures…
CSV (Comma Separated Values) files are the most commonly used file format for importing and exporting big datasets. The reason why a CSV file is preferred over an Excel file is that a CSV file consumes less memory as compared…
Data science is used in all fields today. Whether it’s social media, marketing, or anything else you’ve heard of, data science is used everywhere. Finance is one of the important domains in the industry, and it also depends on data…
The introduction of online payment systems has helped a lot in the ease of payments. But, at the same time, it increased in payment frauds. Online payment frauds can happen with anyone using any payment system, especially while making payments…
An algorithm is a sequence of steps to solve a problem. In computer science, the efficiency of an algorithm depends on how well it organizes data appropriately. The organization of data to solve a particular problem is known as a…
Python has been one of the highest demanded programming languages for the past five years in the industry. Almost every popular website uses Python either in the front-end or the back-end. So if you want to know about some of…
If you are learning Data Science and find it hard to create a dataset for practice from scratch, you can either download a dataset from Kaggle or create fake data. If you want to learn how to create a dummy…
Variance, covariance, and correlation are statistical measures for finding the relationship between data points in a dataset. If you are learning data science, you need to understand these terms. So if you want to learn more about variance, covariance, and…
Flipkart is one of the most popular Indian companies. It is an e-commerce platform that competes with popular e-commerce platforms like Amazon. One of the most popular use cases of data science is the task of sentiment analysis of product…
Most students learn coding to get a job. But sometimes it takes a long time to complete the courses and other skills required to get your first job. So what should you do as a student if you want to…
The execution or running time of the program indicates how quickly the output is delivered based on the algorithm you used to solve the problem. To calculate the execution time of the program, we need to calculate the time taken…
Whenever you have seen a roadmap to learn data science, you must have found people often highlighting Python or R. Python and R are the most popular programming languages among the data science community. But just having the practical knowledge…
Netflix is one of the most popular OTT streaming platforms. It offers a vast collection of television series and films and owns its productions known as Netflix Originals. People who are highly active in stock market investments always keep an…
Sentiment analysis means extracting, identifying, or classifying sentiment from text using natural language processing. It is also known as opinion mining. If you’re looking for some of the best sentiment analysis project ideas, this article is for you. In this…
There are so many code editors for Python that you can use as a student or a professional Python developer. If you want to know about the best code editors for Python, this article is for you. In this article,…
Cuss Words are the words that make your language sound very impolite, rude, and culturally offensive. Sometimes we need to identify and remove cuss words from a piece of text. So if you want to learn to remove cuss words,…
Tipping waiters for serving food depends on many factors like the type of restaurant, how many people you are with, how much amount you pay as your bill, etc. Waiter Tips analysis is one of the popular data science case…
Text classification is a machine learning technique used to classify texts based on predefined labels. For example, classifying languages based on a dataset containing different languages with predefined labels. Text classification is used in various problems of natural language processing…
Finding duplicate values from an array or any other data structure is one of the popular coding interview questions that you can get in any coding interview. The Python programming language provides many inbuilt functions to find the duplicate values,…
There are so many popular programming languages you can learn. Some languages will help you get your first job, while others can help you land your desired job role. So which programming languages should you learn in 2022? In this…
Data Science is one of the best and most competitive careers today. To work as a data science professional in any field, you need to work on projects that showcase most of your skills and approaches to solving business problems.…
You must have heard about some machine learning algorithms before, but most beginners often get confused about how many machine learning algorithms they need to learn when they see professionals using algorithms (specifically in Kaggle) that they haven’t heard about…
A histogram contour plot is a two-dimensional representation of a histogram that looks like a contour plot. It is used to analyze anomalies and manage overplotting in a large dataset. If you don’t know how to visualize a histogram contour…
Decoding a QR code means finding the value, number, text or link behind the QR code. There are many ways to decode a QR code used by your smartphone cameras, which helps you scan a QR code while making online…
Time series analysis means analyzing and finding patterns in a time series dataset. A time-series dataset is a sequence of data collected over an interval of time. Stock price data, monthly sales data, daily rainfall data, hourly website traffic data…
Python is one of the most popular programming languages today. In 2022, Python will be used more in the industry with programming languages like Golang and JavaScript. If you are looking for a job as a Python developer, the first…
Natural Language Processing (NLP) is a subset of machine learning in which we aim to train computers to understand human languages. The chatbot you see in a banking app, Siri on iPhone, or Google translator are examples of natural language…
A time-series graph is a line plot that displays trends or patterns over a dataset collected over an interval of time. For example, when you visualize a line plot of the daily sales made by a business, you are visualizing…
A QR Code is a scannable code used to store information. QR codes are used to redirect you to a specific page or to show you some information. You must have scanned QR codes once in your life when making…
In machine learning, classification means categorizing the known classes, For example, categorizing the most profitable and non-interested customers from a dataset for advertising a particular product. You must have trained a classification model with a machine learning algorithm before. Here…
Time series analysis is one of the most important topics in data science. Time series data is a sequence of data points collected and indexed based on an interval of time, and when we analyze such data to find patterns…
A neural network is a computational architecture that connects an input layer to the output layer. Learning about Neural Networks will not only help you in solving complex Deep Learning problems but will also help you do better in an…
A neural network is a computational structure that connects an input layer to an output layer. This computational structure is used in training deep learning models that can easily outperform any classical machine learning algorithm. As a data science beginner,…
Visualizing data is one of the most valuable skills every Data Scientist and Analyst should have. There are a lot of data visualizations to learn in data science. So if you are a beginner in data science and want to…
Tokenization is the first step you should perform after collecting a textual dataset in every problem based on Natural Language Processing. Sentence and Word tokenization are two different strategies of tokenization that you should know. In this article, I will…
LSTM stands for Long Short Term Memory Networks. It is a type of recurrent neural network that is commonly used for regression and time series forecasting in machine learning. It can memorize data for long periods, which differentiates LSTM neural…
Facebook is one of the most popular social media platforms that owns other popular social media platforms like Instagram and WhatsApp. Facebook is one of those companies where every software engineer and data scientist wants to work. If you want…
Deep Learning is a subset of machine learning that mimics the human brain to solve complex problems. Deep Learning is used to train computers to perform tasks where humans are good at, but computers are not. If you are learning…
Deep Learning is a subset of machine learning where we need a large amount of data to train powerful models capable of finding relationships in data to solve complex problems. While machine learning algorithms can also be used to train…
A machine learning algorithm is used to find relationships between features and labels. Features are the independent variables that we feed into an algorithm to train a machine learning model, and labels are the dependent variables that we aim to…
Query data means requesting specific data from a dataset. If you are familiar with SQL, you must know what it means to query data, but if you use the pandas library in Python, you can still query data from your…
You must have heard or invested in any cryptocurrency once in your life. It is a digital medium of exchange that is encrypted and decentralized. Many people use cryptocurrencies as a form of investing because it gives great returns even…
You must have heard that JavaScript is currently the most popular programming language, and Python is one of the popular languages among Data Scientists. Just like that, every programming language is being used in the industry somewhere it is best.…
In Data Science, Time Series data is a sequence of data points collected and indexed according to time. When we analyze such kinds of data to find patterns over an interval of time, it is known as Time Series Analysis.…
The activation function is a function used in neural networks to calculate the weighted sum of inputs and biases, which is used to determine whether a neuron should be activated or not. You must have heard a lot about activation…
A box plot is a statistical data visualization technique for analyzing the distribution and patterns of numerical data points of a dataset. It represents quartile 1, quartile 3, median, maximum and minimum data points of a feature which helps to…
As machine learning practitioners, we need to collect stock price data for regression analysis and time series analysis. We can easily download it from Yahoo Finance. But imagine if we want to create an application where we can analyze the…
Stress, anxiety, and depression are threatening the mental health of people. Every person has a reason for having a stressful life. People often share their feelings on social media platforms like on Instagram in the form of posts and stories,…
Data Analysis is the process of working with data to gather useful insights that can be used for decision making and solving various business problems. Most of the success stories you hear about companies today are because they have a…
In Data Science, Time Series Analysis is a method of analyzing data collected over an interval of time. Stock price data and covid-19 cases data are examples of time-series data. Time Series Analysis helps understand the underlying causes of trends…
There are so many Python libraries for data science out there today that you will get the simplest alternative of almost any library. As a data scientist, you need to keep improving your skills, so you need to keep learning…
A candlestick chart is a data visualization tool used to analyze the price movements of stocks, cryptocurrencies, currencies, and other financial instruments. If you work as a data scientist/analyst in the finance domain, a candlestick chart is one of the…
Finding the length of a string means counting the number of letters in a string. Python has a built-in len() function for this task, but what if you get a coding interview question to find the length of a string…