Humans take no effort to distinguish a dog, cat, or flying saucer. But this process is quite difficult for a computer to emulate: it only looks easy because God designs our brains incredibly well to recognize images. One common example…
Data science and machine learning can often require an overwhelming amount of skill. However, after exploring a lot of data science skills, in this article, I wanted to share five common data science skills that all Data Scientists should know.…
Imagine a big pile of data, what does that tell you? Data collections are expected to continue to grow day by day, as is the time to give once again. This leads to unsupervised data storage, which has two obvious…
Linear algebra is one of the most important topics in machine learning. In this article, I will introduce you to the basic concepts of linear algebra for machine learning using NumPy. Why Linear Algebra for Machine Learning? Machine learning and…
Machine learning in business problems finds its place in all aspects of IT, from social media to complex financial applications. Machine learning can be used to improve the customer experience, better manage and predict the outcomes of complex data, and…
In this article, I will take you through a very famous case study for machine learning practitioners which is to predict titanic survival with Machine Learning. I will first introduce you to this case study and then I will show…
In this article, I’m going to take you through an in-depth review of BERT in Machine Learning for word embeddings produced by Google for Machine Learning. Here I’ll show you how to get started with BERT in Machine Learning by…
If you have finished with most of the basics in Python and probably thinking about what’s next? Then it’s time to use your skills or analyse your skills by working on some python projects for beginners. In this article, I…
IDEs are very important for running your code with a better experience. An Integrated Development Environment (IDE) generally consists of a code editor, a compiler or an interpreter, and a debugger which is accessible through a single graphical user interface…
When analyzing and modelling data, a significant amount of time is spent preparing the data: loading, cleansing, transforming, and reorganizing. These tasks are often reported to take 80% or more of an analyst’s time. Sometimes the way data is stored…
Text Summarization involves condensing a piece of text into a shorter version, reducing the size of the original text while preserving key information and the meaning of the content. Since manual text synthesis is a long and generally laborious task,…
Web Scraping is a specialized tool designed to quickly and accurately extract data from any web page. Web scraping tools vary greatly in terms of design and complexity, depending on the project. The need for web scraping is to collect…
How quickly things change when you are in the age of machine learning and artificial intelligence. We have seen Cloud computing evolving from a risky and confusing system to a very important strategy that organizations, doesn’t matter large and small…
In Machine Learning, the Stemming process is widely used in tagging, indexing, SEO, web search results and information search. For example, the search for fish on Google will also result in fish, fishing as fish is the root of the…
In Machine Learning, a decision tree is a decision support tool that uses a graphical or tree model of decisions and their possible consequences, including the results of random events, resource costs, and utility. This is a way of displaying…
In this article, I will take you through, how you can visualize real-time stock price data with Python by using the Yahoo finance API known as yahoo_fin. I will use the Plotly package in python to visualize real-time stock price…
Detection of emotions means recognizing the emotional state of a person – for example, anger, confusion or deception on vocal and non-vocal channels. The most common technique analyzes the characteristics of the voice signal, with the use of words as…
Contact tracing is a process used by public health ministries to help stop the spread of infectious disease, such as COVID-19, within a community. In this article, I will take you through the task of contact tracing with Machine Learning.…
Today, Competitive Programming is more popular than ever. The Internet has played an important role in this progress. There is now an active online community of competitive programmers and there are many competitions that take place every week. At the…
The term hate speech is understood as any type of verbal, written or behavioural communication that attacks or uses derogatory or discriminatory language against a person or group based on what they are, in other words, based on their religion,…
PyTorch is a Python library that facilitates the creation of deep learning models. PyTorch is very flexible and easy to use for deep learning tasks. The accessibility and friendliness of early adopters in the years that followed its first publication,…
A bot is a software application programmed to perform certain tasks. The robots are automated, which means that they operate according to their instructions without a human user needing to start them. Bots often mimic or replace the behaviour of…
Bubble plots are better versions of the scatter plots, replacing the dots with bubbles. Most often, a bubble plot displays the values of three numeric variables, with the data for each observation represented by a circle (“bubble”), while the horizontal…
In this article, I’ll walk you through scraping Twitter with Python without API using the twint module, and I’ll also analyze some relationships based on followings and mentions among a group of Twitter users. One of the hot topics in…
In this article, you will learn how to create a unique password generator app using python in a few simple steps. I will first create a program to generate unique passwords. Next, I will show you how we can turn…
Deep learning is a subset of Artificial Intelligence, which is an area that relies on learning and improving on its own by examining computer algorithms. While machine learning uses simpler concepts, these models work with artificial neural networks, designed to…
Emotion detection involves recognizing a person’s emotional state – for example, anger, confusion, or deception on vocal and non-vocal channels. The most common technique analyzes the characteristics of the speech signal, with the use of words as additional input, if…
Text to speech is the generation of speech synthesized from the text. The technology is used to communicate with users when reading a screen is not possible or impractical. This not only opens up apps and information to use in…
In this article, I’ll walk you through how to create a fashion recommendation system with Machine Learning that will work like highly personalized online shopping recommendations. But before you go ahead, you need to know what a recommendation system is.…
Machine learning is fast becoming one of the most important developments in the software industry. Although this cutting edge technology has been around for decades, it is now becoming commercially viable. We are in an era where machine learning techniques…
Geospatial data shows a number of interesting features. Interactive visualization of geospatial data can provide a wealth of information about the data and area and much more functionality in the data. Python has so many packages to visualize geospatial data.…
Google Trends is a keyword research tool that helps the researchers, bloggers, digital marketers and some more people in the digital industry to find how often a keyword is entered into Google search engine over a given period. Google Trends…
One of the great advantages of being in the programming route is that you can work for yourself to earn money with programming. Unlike other businesses, you don’t need a good startup or a team, you just need a laptop…
To visualize the features of different categories we use bar charts which are a very simple way of presenting the features. But when we are having a lot of features in one category only then a bar chart will not…
If you are a newbie to data science and want to explore it for your first Data Science Project, then in this article I will introduce you to a beginner level data science task. Most of the recent growth in…
User interface (UI) is the point where a User Interacts with a Machine using Mouse, Keyboard, or even touch screens and other input sources. The goal of an effective user interface is to make the experience of a user very…
Sentiment analysis is the process by which all of the content can be quantified to represent the ideas, beliefs, and opinions of entire sectors of the audience. The implications of sentiment analysis are hard to underestimate to increase the productivity of…
Data science and data engineering are two different branches of big data paradigm – an approach in which enormous speeds, varieties and volumes of structured, unstructured and semi-structured data are captured, processed, stored and analyzed using a set of techniques…
Natural Language Processing (NLP) consists of developing applications and services capable of understanding human languages. Some practical examples of NLP are speech recognition, for example, Google voice search, understanding content or analyzing feelings, etc. Use of Natural Language Processing (NLP)…
The most likely way for attackers to gain access to your infrastructure is through the network. Network security is the general practice of protecting computer networks and devices accessible to the network against malicious intent, misuse and denial. In this…
No discussion of machine learning would be complete without a section devoted to Machine Learning Algorithms. Algorithms are a set of instructions for a computer on how to interact with, manipulate and transform data. What Are Machine Learning Algorithms? An…
Due to the affordable computing power and the importance of data in decision making Machine Learning in Finance is getting very useful to make financial and investment decisions with great accuracy. The use of Machine Learning in Finance is reshaping…
The LSTM Network model stands for Long Short Term Memory networks. These are a special kind of Neural Networks which are generally capable of understanding long term dependencies. LSTM model was generally designed to prevent the problems of long term…
The combined knowledge of statistics, data mining, and machine learning plays a major role in understanding the data and describing the data features to find the relationships and patterns between the data so that we can build a model for…
Wikipedia is one of those largest platforms which provides almost every information for free. From your kindergarten till today, you must have visited this platform atleast once to get any information from school presentations to professional research, Wikipedia helps everybody.…
Have you ever tried to translate any text using google, it’s straightforward and helpful to do so when I used to study the German Language google helped me alot in my homework. Do you know how Google does that? Google…
The role of Analytics in an Organisation has completely changed over the years. Earlier the higher-level officers and Board Members used to make the most decisions based on their experience and knowledge. But now the statistics and historical performance are…
Candlestick Chart is a powerful way to visualize the trends and changes in the stock market and other financial instruments. Most people use a Candlestick chart to visualize the trading patterns. This article will take you through how you can…
Stock Price Prediction means to determine the future value of the stocks or other financial instruments of an organisation. If you master the art to predict stock prices, you can earn a lot by investing and selling at the right…
Big Data is a type of data that is in a huge quantity and is still growing rapidly. It is so large and complex that it is impossible to manage it using the traditional ways of computing and to store…
The Classes in Python are the main tool used for Object-Oriented Programming (OOP). A Class is a coding structure and a specific tool to implement new kinds of objects in Python that supports inheritance. OOP offers a very different and…
Web Scraping means to collect data from the Internet. As a beginner in data science, you must have seen CSV files on the Internet distributed by some popular websites like Kaggle and other govt websites. The data is prepared by…
When most people hear Machine Learning, they picture a robot, a dependable butler or a deadly Terminator, depending on who you ask. But Machine Learning is not just a futuristic fantasy; it’s already here. It has been around for decades…
When you make an accurate prediction using your trained Machine Learning model, then the next step is often to measure the performance of your model. Data Scientists and other Machine Learning Experts spend a larger part to evaluate a Machine…
AdaBoost Algorithm is a boosting method that works by combining weak learners into strong learners. A good way for a prediction model to correct its predecessor is to give more attention to the training samples where the predecessor did not…
So I am a part of a WhatsApp group named as “Data Science Community”, recently I thought to explore the chat of this group and do some analysis on it. So, here in this article, I will take you through…
An Algorithm is a series of steps that helps in solving specific problems. Machine Learning Algorithms helps us in providing mathematical equations which help in predicting the future by using the past behaviour of the data. There is no algorithm…
Named Entity means anything that is a real-world object such as a person, a place, any organisation, any product which has a name. For example – “My name is Aman, and I and a Machine Learning Trainer”. In this sentence…
ARIMA model means Autoregressive Integrated Moving Average. This model provides a family of functions which are a very powerful and flexible to perform any task related to Time Series Forecasting. In Machine Learning ARIMA model is generally a class of…
Fraud is one of the major issues we come up majorly in banks, life insurance, health insurance, and many others. These major frauds are dependent on the person who is trying to sell you the fake product or service, if…
The Random Forest algorithm is an ensemble of the Decision Trees algorithm. A Decision Tree model is generally trained using the Bagging Classifier. If you don’t want to use a bagging classifier algorithm to pass it through the Decision Tree…
Have you ever faced problems in getting started with Data Science and Machine Learning? If you are doing a course from a very respective university still you face problems with lack of concepts and knowledge of the basics. So you…
Indeed, two people can never have the same fingerprints, it is unique in every human. But using fingerprints we can classify gender, whether it’s male or female. In this article, I will take you through a Gender Classification Model which…
In this article, I will show you, 5 Beginner, to Intermediate level Artificial Intelligence Projects. Artificial Intelligence consists of three main components, which are Data Science, Machine Learning, and Deep Learning. All the projects are solved and explained. If you…
Machine Learning and Artificial Intelligence are the most searched content on the Internet among the programmers coming from different programming languages. The popularity of Machine Learning has led to a lot of research that today we have even reached to…
In this article, I will show you 5 beginner level Machine Learning Projects for Beginners. All the projects are solved and explained. If you are new to Machine Learning and want to improve yourself more before getting into projects you…
A dictionary is an example of a key-value store also known as Mapping in Python. It allows you to store and retrieve elements by referencing a key. As dictionaries are referenced by key, they have very fast lookups. As they…
Have you ever got confused when you try to choose the best algorithm for a machine learning task? Suppose you are planning to buy a new car. Your planning is never going to be as short as moving to the…
Suppose you have trained a lot of classification models, and your each model is achieving the accuracy of 85 percent. A very simple way to create an even better classifier is to aggregate the predictions of each classifier and predict…
As one of the most basic functions in programming, loops are an important piece to nearly every programming language. Loops enable developers to set certain portions of their code to repeat through several loops, referred to as iterations. This topic…
You must have seen many articles and tutorials on web scraping. Even I have written an article on it. In this article, I will do something different, that is scraping Instagram with Python. It is an easy task until you…
The general goal of a classification model is to find a decision boundary. The purpose of the decision boundaries is to identify those regions of the input class space that corresponds to each class. In this article, I will take…
Data types are variables that are used to store values. In Python, variables do not need a pre declaration; the declaration of variables in Python happens automatically when we assign any value to a variable. Just like variables, data types…
Anomaly Detection means detecting unexpected events in the dataset which differ from the norm. Anomaly Detection is very often used in unlabeled data. There are two most important assumptions in the task of Anomaly Detection: the first assumption says that…
The Ridge Regression is a regularized version of a Linear Regression. The Ridge Regression enables the machine learning algorithms to not only fit the data but also to keep weights of the model as small as possible. It is quite…
Machine Translation is one of the most challenging tasks in Artificial Intelligence that works by investigating the use of software to translate a text or speech from one language to another. In this article, I will take you through Machine…
Audio Feature Extraction has been one of the significant focus of Machine Learning over the years. The most frequent common state of data is a text where we can perform feature extraction quite smoothly. Then we have Feature Extraction for…
What will you do if your data is a bit more complicated than a straight line? A good alternative for you is that you can use a linear model to fit in a nonlinear data. You can use the add…
Gradient Descent is an optimisation algorithm which is capable of providing optimal performance to a wide range of tasks in Machine Learning. The idea behind a Gradient Descent algorithm is to tweak the parameters using loops to minimize the cost…
The Receiver Operating Characteristic (ROC) curve is a popular tool used with binary classifiers. It is very similar to the precision/recall curve. Still, instead of plotting precision versus recall, the ROC curve plots the true positive rate (another name for…
In Machine Learning, Precision and Recall are the two most important metrics for Model Evaluation. Precision represents the percentage of the results of your model, which are relevant to your model. The recall represents the percentage total of total pertinent…
Testing and Validation are the only way to know how well a model will generalize to new cases is to actually try it out on new cases. One way to do that is to put your model in production and…
OpenAI Gym is a toolkit that provides a wide variety of simulated environments (Atari games, board games, 2D and 3D physical simulations, and so on), so you can train agents, compare them, or develop new Machine Learning algorithms (Reinforcement Learning).…
Image filtering is used to enhance the edges in images and reduce the noisiness of an image. This technology is used in almost all smartphones. Although improving an image using the image filtering techniques can help in the process of…
Data Visualisation plays a major role to study and analyse data to extract useful insights that can add value to our end task. Python being a universal language provides a lot of libraries for almost every task you have ever…
In this article I will take you through a Trading Strategy with Machine Learning, which can be used to determine when you should buy stocks and when you should sell. Generally it is not easy to predict stock market, but…
There are so many different types of Machine Learning systems that it is useful to classify them in broad categories, based on the following criteria: Whether or not they are trained with human supervision (supervised, unsupervised, semisupervised, and Reinforcement Learning)…
I recently shared an article on Audio Processing with Python. It was about how you can process and manipulate an audio file with Python. If you have gone through that, now you must know about how the basic stuff of…
In this article, I will take you through a brief explanation of Image Segmentation in Deep Learning. I will only explain the concept behind the image segmentation here in this article. If you want to go through the practical part…
Machine Learning is a Very Broad Field. If Machine Learning is a dish, then linear algebra, programming, analytical skills, statistics, and Algorithms are the primary recipes of Machine Learning. If you will go more deep inside the Machine Learning concepts,…
Sometimes, while doing programming, we need to go through some audio processing stuff. Some of the most used audio processing tasks in programming include – loading and saving audio files, splitting and appending the audio files into segments, creating mix…
Have you ever thought how Snapchat manage to apply amazing filters according to your face? It have been programmed to detect some marks on your face to project a filter according to those marks. In Machine Learning those marks are…
Being a practitioner in Machine Learning, you must have gone through an image classification, where the goal is to assign a label or a class to the input image. Now, suppose you want to get where the object is present…
Machine Learning Pipelines performs a complete workflow with an ordered sequence of the process involved in a Machine Learning task. In most of the functions in Machine Learning, the data that you work with is barely in a format for…
TensorBoard is a great interactive visualization tool that you can use to view the learning curves during training, compare learning curves between multiple runs, visualize the computation graphs, analyze training statistics, view images generated by your model, visualize complex multidimensional…
Where Binary Classification distinguish between two classes, Multiclass Classification or Multinomial Classification can distinguish between more than two classes. Some algorithms such as SGD classifiers, Random Forest Classifiers, and Naive Bayes classification are capable of handling multiple classes natively. Others…
Most of the keyboards in smartphones give next word prediction features; google also uses next word prediction based on our browsing history. So a preloaded data is also stored in the keyboard function of our smartphones to predict the next…
Data Augmentation is a technique in Deep Learning which helps in adding value to our base dataset by adding the gathered information from various sources to improve the quality of data of an organisation. Data Augmentation is one of the…
Binary Classification is a type of classification model that have two label of classes. For example an email spam detection model contains two label of classes as spam or not spam. Most of the times the tasks of binary classification…
You must have seen a cloud filled with words in a lot of Analysis tasks and machine learning projects. A WordCloud represents the importance of each word in a set of words by analyzing the frequency of terms. In this…
In this article you will learn to create databases, manipulate databases, and will also learn some operations on handling databases in MySQL with Python. You need to download and install MySQL from here, and after installing MySQL you also need…
Birds inspired us to fly, nature inspired us to countless inventions. It seems logical, then to look at the brain’s architecture for inspiration on how to build an Intelligent Machine. This is the logic that sparked Artificial Neural Networks (ANN).…
There are two main approaches to training models across multiple devices; model parallelism, where the model is split across the devices, and data parallelism, where the model is replicated across every device, and each replica is trained on a subset…
In this article I will show you how you can create your own dataset by Web Scraping using Python. Web Scraping means to extract a set of data from web. If you are a programmer, a Data Scientist, Engineer or…
An AI Chatbot is one of the most achieved goals in the field of Artificial Intelligence. Today Chatbot can help you in every way from assisting you to order something online to guide you through a Business Plan. Every Brand…
In this article, I will take you through a very powerful algorithm in Machine Learning, which is the Grid Search Algorithm. It is mostly used in hyperparameters tuning and models selection in Machine Learning. Here I will teach you how…
In this article, we will look at how to speed up your models by using a GPU. We will also see how to split the computations across multiple devices, including the CPU and numerous GPU devices. Thanks to GPUs, instead…
Natural Language Processing or NLP is a field of Artificial Intelligence which focuses on enabling the systems for understanding and processing the human languages. In this article, I will use NLP to analyze my WhatsApp Chats. For some privacy reasons,…
PyTorch is a library in Python which provides tools to build deep learning models. What python does for programming PyTorch does for deep learning. Python is a very flexible language for programming and just like python, the PyTorch library provides…
In Data Science, you must have seen people reading CSV files and excel files to work with the data, but what about a PDF. Python is a very high level language that is the reason it is mostly getting used…
Machine Learning has been an outstanding achievement in the field of Artificial Intelligence. The algorithms behind the success of Machine Learning are Deep Neural Networks which were made after research of years through the expert researchers. The only difficulties the…
If you want to deploy your TensorFlow model to a mobile or embedded device, a large model may take too long to download and use too much RAM and CPU, all of which will make your app unresponsive, heat the…
I have trained and developed a lot of Machine Learning models, if you are a student in Machine Learning, you must have also developed models. In this article, I will train and Deploy a Machine Learning Model using Flask step…
PySpark is the API of Python to support the framework of Apache Spark. Apache Spark is the component of Hadoop Ecosystem, which is now getting very popular with the big data frameworks. Apache Spark is a very powerful component which…
According to the report of Centers of Disease Control and Prevention about one in seven adults in the United States have Diabetes. But by next few years this rate can move higher. With this in mind today, In this article,…
Many clustering algorithms are available in Scikit-Learn and elsewhere, but perhaps the simplest to understand is an algorithm known as k-means clustering, which is implemented in sklearn.cluster.KMeans. Introduction The k-means algorithm searches for a pre-determined number of clusters within an unlabeled…
This article features the implementation of an employee turnover analysis that is built using Python’s Scikit-Learn library. In this article, I will use Logistic Regression and Random Forest Machine Learning algorithms. At the end of this article, you would be…
If you want to find out who are your best customers, using an old technique RFM matrix principle is still the best in the business. RFM means – Recency, Frequency and Monetary. RFM is basically a customer segmentation technique that…
Many Business activities are seasonal in nature, where most of the business are dependent on a particular time of festival and holidays. Every business uses sales promotion techniques to increase the demand for their products and services, in order to…
TensorFlow is a powerful library for numerical computation, particularly well suited and fine-tuned for large–scale Machine Learning ( but you could use it for anything else that requires heavy calculations). The Google Brain team developed it, and it powers many…
Reinforcement Learning (RL) is one of the most exciting fields of machine learning today. and also one the oldest. It has been around since the 1950s, producing many exciting applications over the years, particularly in games (e.g., TD-Gammon, a Backgammon-playing…
Merging Datasets is one of the most high-performance features, which is provided by pandas in Python. In this article, I will show how we can merge datasets in Python with the help of examples and real-world scenarios. For convenience, I…
Evaluating a model is simple enough to use a test set. But suppose you are hesitating in model selection between two types of models (say, a linear model and a polynomial model); how can you decide between them? One option…
There is a lot of difference between the data you get to practice data science skills and the data you get in the real world. Honestly speaking, many datasets you will get in the process of actual-world data science tasks…
This article is about description for those who need to know what is the actual difference between the dataset split between the Training and Test sets in Machine Learning while training and classifying models. What is Training Data? All the…
Rotating, re-orienting, or stretching the piece of paper in three-dimensional space doesn’t change the flat geometry of the article: such operations are akin to linear embeddings. If you bend, curl, or crumple the paper, it is still a two-dimensional manifold,…
In this article, you will explore what is perhaps one of the most broadly used of unsupervised algorithms, principal component analysis (PCA). PCA is fundamentally a dimensionality reduction algorithm, but it can also be useful as a tool for visualization,…
Below are some of the famous Data Science books that will help beginners explore more about Data Science and the experienced practitioners to gain more deep knowledge. I found these books really useful and highly recommended. Best Data Science Books…
Data Science and Data Analysis have been around a lot this year. For students who are looking for a long term career, both Data Science and Data Analysis jobs have been a good option for them. We will see this…
Decision Trees are versatile Machine Learning algorithms that can perform both classification and regression tasks, and even multi-output tasks. They are powerful algorithms, capable of fitting complex datasets. Decision trees are also the fundamental components of Random Forests, which are…
Support vector machines (SVMs) are a particularly powerful and flexible class of supervised algorithms for both classification and regression. In this article, I will develop the intuition behind support vector machines and their use in classification problems. I will begin…
In Machine Learning Naive Bayes models are a group of high-speed and simple classification algorithms that are often suitable for very high-dimensional datasets. Because they are so fast and have so few tunable parameters, they end up being very useful…
This Workflow can guide you through your Machine Learning Projects. There are eight main steps: Frame the problem and look at the big picture. Get the data. Explore the data to get insights. Prepare the data to better expose the…
What is a Neural Network Neural Network is a computational algorithm that is used in creating deep learning models for predictions and classifications. It is based on self-learning and training, rather than being explicitly programmed. Neural Networks are inspired by…
In the real world, data rarely comes in perfect form. With this in mind, one of the more critical steps in using machine learning in practice is Feature Engineering, that is, taking whatever information you have about your problem and turning…
Machine Learning interview questions are an essential part of an interview as a Data Scientist. Here I have created a set of Machine Learning interview question with there answers along. With these questions and solutions, you will be able to…
Before learning Seaborn, you should know that matplotlib has proven to be an incredibly useful and popular visualization tool, but even avid users will admit it often leaves much to be desired. There are several valid complaints about Matplotlib that…
I have covered a lot of ground so far, and you now know that Machine Learning is really about, why it is useful, what some of the most common categories of Machine Learning systems are, and what a typical project…
Let’s train and run a Linear regression model to make Predictions, In this article, I will load the data, prepare it, create a scatter plot for visualization, and then train a linear regression model to make a prediction. I will…
When most people hear Machine Learning, they picture a robot, a dependable butler or a deadly Terminator, depending on who you ask. But Machine Learning is not just a futuristic fantasy; it’s already here. It has been around for decades in…
One of the best things about the scikit-learn library in python is that it provides four steps modeling patterns that make it easy for the programmer to train a machine learning classifier. In this article, I will use Logistic Regression…
Time Series Analysis carries methods to research time-series statistics to extract statistical features from the data. Time Series Forecasting is used in training a Machine learning model to predict future values with the usage of historical importance. Time Series Analysis is broadly speaking used in training machine learning models for the Economy, Weather forecasting, stock price prediction, and additionally in Sales forecasting. It can be said that Time Series Analysis is widely used in facts based on non-stationary features. Time Series Analysis and…
If you are planning to start with Data Science, Machine Learning and AI, then determining the best programming language is not an easy task for you. If you will consider taking any advice from your seniors, then you might get…
Using the Folium Library in Python we can easily Plot Geographical data on a Map. Your analysis will be much more valuable if you visualized them the right way. A perfectly visualized data helps in drawing the changes and trends…
Skin Cancer is one of the most common types of disease in the United States. Up to 4 Million cases have been reported dead due to skin cancer in the United States over the year. In this article, I will…
If you know enough statistics, programming especially python, Machine Learning, etc, one thing you should know that still getting a job in Data Science is a difficult task. Some people may have the best skill set, but one thing that…
Using the HOG features of Machine Learning, we can build up a simple facial detection algorithm with any Image processing estimator, here we will use a linear support vector machine, and it’s steps are as follows: Obtain a set of…
In this article, you’ll learn how to create a bar chart race animation such as the one above using the matplotlib data visualization library in python. Bar chart races have been around for quite some time. This year, they’ve taken…
The Google Play Store apps data analysis provides enough potential to drive apps making businesses to succeed. Actionable stats can be drawn for developers to work on and capture the Android market. The data set that I have taken in…
This Article is about Data Science and Machine Learning with Python. You will also get to work on Hands-on Projects at the end of this Article. You can download Python from python.org. But if you don’t want to download Python,…
Spacecraft and satellites operating in deep space can generate huge amounts of data due to the complexity of their research missions. Because of the different rotations and orbits of their host planets, these massive data packets must be transmitted to…
Introduction to CNN Convolutional neural networks (CNN) are primarily used to classify images or identify pattern similarities between them. So a convolutional network receives a normal color image as a rectangular box whose width and height are measured by the…
Social Network Analysis is one of the important topics of Machine Learning. A basic step for social network analysis is to encode the data into low dimensional representations. Social networks have greatly facilitated communication between web users around the world.…
In this Article I will create a Linear Regression model and a Decision Tree Regression Model to Predict Google Stock Price using Machine Learning and Python. Download the data set Import pandas to import a CSV file: To get the…
Understanding GDP Gross domestic product (GDP) at current prices is the GDP at the market value of goods and services produced in a country during a year. In other words, GDP measures the monetary value of final goods and services…
Twitter Sentiment Analysis is the process of computationally identifying and categorizing tweets expressed in a piece of text, especially in order to determine whether the writer’s attitude towards a particular topic, product, etc. is positive, negative, or neutral. In this Article…
This Article is based on SMS Spam detection classification with Machine Learning. I will be using the multinomial Naive Bayes implementation. This particular classifier is suitable for classification with discrete features (such as in our case, word counts for text classification). It…
If you are a programmer, and moving towards Machine Learning and Artificial Intelligence, you should know that the algorithms of machine learning, deep learning and AI consumes a lot of power of a processor. For better results you should work…
Yolo v3 Object Detection in Tensorflow full tutorial What is Yolo? Yolo is a deep learning algorithm that uses convolutional neural networks for object detection.So what’s great about object detection? In comparison to recognition algorithms, a detection algorithm does not…
In this article, I will show how we can do Weather Forecasting with Machine Learning algorithm and compare some frameworks for further classification. Lets start this task by importing the libraries Download and read the data set To look at…
The term artificial intelligence stirs emotions. For one thing there is our fascination with intelligence, which seemingly imparts to us humans a special place among life forms. Questions arise such as What is intelligence?, How can one measure intelligence? or…
In this article, I will create a model for credit card fraud detection using machine learning predictive model Autoencoder and python. Lets start with importing libraries The data set I am going to use contains data about credit card transactions that…
In this article, I will show you, the most advanced interactive visualizations techniques for Data Science, using python, plotly and bar chart race. I will use the Electricity power consumption Data set for this tutorial. I will analyse the power…
Virtual Reality is a term used for computer-generated 3D environments that allow the user to enter and interact with alternate realities. The users are able to immerse themselves to varying degrees in the computer’s artificial world which may either be…
Roadmap to Data Scientist
This article is all about Matplotlib, the basic data visualization tool of Python programming language for Data Science. Here I will discuss various plot types with Matplotlib and customization techniques associated with Data Science. Introduction to Matplotlib Matplotlib is the basic…
Pandas Tutorial
NumPy Tutorial
Statistics Tutorial with Python
All Machine Learning Algorithms with Scikit-Learn
Introduction to Machine Learning
Introduction to Data Science
Exploratory Data Analysis on Indian Premier League
Risk Analysis of Mutual Funds Investments
Data Science and Machine Learning Projects
Suicides in India Analysis
World Happiness Report - 2019
Air Quality Exploration for Data Science Beginners
k-Nearest Neighbors with Python
Olympic Games Data Exploration
Human Activity Recognition using Smartphone Data
Crime Analysis with Python
Prediction of Customer Churn with Machine Learning
GDP Analysis with Python
Supermarket Sales Analysis with Python
Movie Reviews Sentiment Analysis
Building a program that uses the dual moving average crossover to determine when to buy and sell stocks
Three Dimensional Bar Plots with Python
Scrape Newspaper Articles using Natural Language Processing.
Classify Clothes using Python and Artificial Neural Networks
Bitcoin Price Prediction for Next 30 Days with Machine Learning
Book Recommendation system using K Nearest Neighbor
DNA Sequencing With Machine Learning
FIFA Analysis with Python
Student marks Performance Analysis with Machine Learning
Covid-19 Analysis with Python
Movie Recommendation System with Machine Learning
Heart Disease Prediction with Machine Learning
Python Tutorial for Web Scraping
Creating an analog clock with python
Virtual Assistant with Python
A collection of some challenging python programs with solutions.
Email Spam detection with Machine Learning
In this tutorial, I will show you how to create a simple and quick chatbot in python using a rule-based approach.
In this tutorial we will create a Accounting Vouchers application using Python and the Kivy language.
Data Science Project on - Amazon Product Reviews Sentiment Analysis using Machine Learning and Python.
Data Science Project on Extracting HOG Features from an Image using Machine Learning.
Classification of Text using Multinomial Naive Bayes
Creating a Sign-in window using Python.
Prediction Apple's Stock Price
In this article, I will build a simple Clock app with python using the kivy module in python, similar in concept to the built-in application found in both iOS and Android using the Python Kivy language. Let’s learn most of…
Data Science Advance Project using Machine Learning
Simple Python Program to detect faces in a Webcam.
Learn about Widgets, labels and buttons in Kivy language
Learn to create desktop and mobile apps with python
Data Science Advance Project on Text and Annotations with python.
Data Science Beginner Project on Area and Population.
Data Science Project on Time Series with python using a Dataset- Fremont Bridge Bicycle Counts.
Data Science Project for Beginners on Birth Rate Analysis with Python.
Data Science project for Beginners on US-President Height using python.
Face Detection using Open Source Computer Vision Library in python.
Covid-19 Analysis on a map using folium library with python.
Creating Graphics in Python using Turtle module.
Classes and Object Oriented Programming in Python
This is the common question of every beginner today that who really uses python?, Which Brands are using Python?
Creating 3D graphs in python with matplotlib
Creating a Student Details GUI application with Python
As there are so many programming languages available today, this is the usual first question of newcomers
Addition, subtraction, multiplication and division between lists in python.
Creating a simple MCQ game with python.
Creating a GUI application for clock in Python
Creating a GUI application for calendar with python
The most simplest program to print Fibonacci series with python
Python Tutorial to get smallest and largest number in a list.
Python tutorial to get odd and even numbers from a list.
The most simplest python program to create a QR code
Python tutorial to print table of any number
Python Tutorial to create a number guessing game
The most simplest python program to get Prime and Composite numbers.
Python full course from beginner to advance