The single most significant gap between a beginner and a pro in machine learning isn’t more courses; it’s hands-on experience. It’s about getting your hands dirty with real-world projects. If you are looking for hands-on projects to become a pro in machine learning, this article is for you. In this article, I have put together a list of over 50 machine learning projects for all levels you should try.
50+ Machine Learning Projects for All Levels
Below is a list of over 50 projects for all levels to become a pro in machine learning. Think of this as your personal project roadmap, designed to help you master everything you need to know.
Beginner Level Projects to Get Started
These projects are your foundation. They’re designed to help you get comfortable with the core workflow of any ML project:
- Music Popularity Prediction
- Loan Approval Prediction
- Credit Score Classification
- House Rent Prediction
- Real Estate Price Prediction
- Clustering Music Genres
- Credit Card Clustering
For these projects, focus on the fundamentals. At this stage, the real learning occurs during data preprocessing.
Intermediate Level Projects to Sharpen Your Skills
Once you’re comfortable with the basics, it’s time to add layers of complexity. These projects introduce you to more advanced topics:
- Building a Recommendation System
- End-to-End Predictive Model
- Hybrid Machine Learning Model
- Image Classification Model with Deep Learning
- Google Search Queries Anomaly Detection
- Anomaly Detection in Transactions
- Food Delivery Time Prediction
- Classification on Imbalanced Data
- Classification with Neural Networks
- Consumer Complaint Classification
- Compare Multiple Predictive Models
- Geospatial Clustering with Python
- Smart Loan Recovery System
- Topic Modelling
- User Profiling and Segmentation
- Multivariate Time Series Forecasting
- Instagram Reach Forecasting
- Analyzing & Forecasting Rainfall Trends
- Next Word Prediction Model
- Building an AI Agent using OpenAI API
- Document Analysis using LLMs
- Packaging ML Models
At this stage, it’s not enough to get a result. Your focus should shift to reproducibility and scalability.
Advanced Level Projects to Demonstrate Your Mastery
This is where you go from a practitioner to a pro. These projects require a deep understanding of multiple domains:
- Building a Live & Shareable ML App
- Dynamic Pricing Strategy
- Demand Forecasting & Inventory Optimization
- Weather Forecasting
- Fine-Tuning LLMs on your own data
- Building a Predictive Keyboard Model with PyTorch
- Building an AI Agent using Agentic AI
- Code Generation Model with LLMs
- Building a Large Language Model from Scratch
- Building a RAG Pipeline for LLMs
- Data Augmentation using LLMs
- Text Completion using Fine-tuning LLMs
- Text Summarization Model with LLMs
- End-to-End Chatbot
- YouTube Video Chaptering
- AI Image Caption Recommendation System
- Generative AI Model From Scratch
- Fashion Recommendations using Image Features
- Synthetic Data Generation
- MLOps Pipeline using Apache Airflow
- Building a Multi-Agent System using CrewAI
- Building Synthetic Medical Records
- AI Image Generation using Diffusion Models
- Building a Diffusion Model from Scratch
For these projects, documentation is key. Learn to document your process as you work on these projects. Your ability to communicate complex ideas is just as important as your ability to code them.
Many of these projects will require you to have a strong knowledge of Machine Learning algorithms. If you are learning ML Algorithms, my book will help you in your journey. Here are links to find the ebook and paperback versions:
Summary
A list is just a list until you take action. The secret to becoming a pro in machine learning isn’t completing all 50 projects; it’s excelling in a handful of them exceptionally well. Please pick one from each level that genuinely excites you, and see it through to the end. So, choose a project, open your editor, and start building.
I hope you liked this article on a list of over 50 machine learning projects for all levels you should try. Feel free to ask valuable questions in the comments section below. You can follow me on Instagram for many more resources.
