ML-CaPsule is a comprehensive, open-source learning hub for aspiring and experienced data science enthusiasts. Whether you lack a mentor or want structured, project-based learning — this repository helps you master Machine Learning, Deep Learning, NLP, Computer Vision, and more through 500+ real-world projects.
💡 No mentor? No problem. Learn by building, become interview-ready, and grow with a thriving open-source community.
 ML Fundamentals |
 Statistics & Analytics |
 Data Science |
| 📈 | Why Machine Learning? | 🗂️ |
| 📚 | Pre-requisites | 📦 |
| ⭐ | Featured Projects | 📂 |
| 🔗 | Useful URLs | 🚀 |
| ⚙️ | Contribution Guidelines | 📖 |
| ✨ | Contributors | ❤️ |
| 🔍 | Notebook Health Check | 📝 |
Machine learning automates analytical model building — enabling systems to learn from data, identify patterns, and make decisions with minimal human intervention. It sits at the heart of modern AI.
| Benefit | Impact |
|---|---|
| 🔍 Pattern Discovery | Uncover hidden trends in massive datasets |
| ⚡ Automation | Reduce manual analysis and repetitive tasks |
| 🎯 Personalization | Power recommendations at Netflix, Amazon & Spotify |
| 🏥 Healthcare | Early disease detection & medical imaging |
| 💼 Business Edge | Used by Google, Meta, Uber as a competitive differentiator |
| Step | Resource | Link |
|---|---|---|
| 1️⃣ | Install Python | python.org |
| 2️⃣ | Learn Python Basics | W3Schools Python ML |
| 3️⃣ | ML with Python Course | freeCodeCamp ML |
🎨 Getting Started with R & RStudio — Click to expand
R is an open-source language built for statistical computing, data analytics, and scientific research.
- Install R → Download from CRAN
- Install RStudio → Download RStudio Desktop
| # | Course | Link |
|---|---|---|
| 1 | R Programming Full Course (freeCodeCamp) | Watch → |
| 2 | R Basics Tutorial (Edureka) | Watch → |
| 3 | Data Science with R (Simplilearn) | Watch → |
| 4 | Intro to R for Data Science (DataCamp) | Watch → |
|
Methods for constructing variable combinations to describe data accurately.
Expose patterns, trends & correlations visually.
Select relevant features to boost model accuracy.
|
Multidisciplinary field combining statistics, ML, computing, and domain expertise to extract insights and drive decisions across industries. |
🗄️ Click to explore all datasets — Classification, Regression, NLP, CV & more
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | Titanic | Predict passenger survival | ⭐ | Kaggle |
| 2 | Iris Flower | Classify 3 iris species | ⭐ | UCI |
| 3 | Breast Cancer Wisconsin | Malignant vs benign tumors | ⭐ | UCI |
| 4 | Heart Disease | Predict from clinical features | ⭐⭐ | UCI |
| 5 | Pima Indians Diabetes | Diabetes onset prediction | ⭐ | Kaggle |
| 6 | Adult Income | Income >$50K prediction | ⭐⭐ | UCI |
| 7 | Bank Marketing | Term deposit subscription | ⭐⭐ | UCI |
| 8 | Wine Quality | Good vs bad wine classification | ⭐ | UCI |
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | Boston Housing | Predict housing prices | ⭐ | Kaggle |
| 2 | California Housing | Median house values | ⭐ | Kaggle |
| 3 | House Prices | 79-variable price prediction | ⭐⭐ | Kaggle |
| 4 | Auto MPG | Fuel efficiency prediction | ⭐ | UCI |
| 5 | Student Performance | Exam score prediction | ⭐ | UCI |
| 6 | Medical Cost | Insurance charge prediction | ⭐ | Kaggle |
| 7 | Bike Sharing Demand | Hourly rental counts | ⭐⭐ | Kaggle |
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | SMS Spam Collection | Spam vs ham classification | ⭐ | UCI |
| 2 | IMDB Reviews | 50K movie sentiment analysis | ⭐ | Kaggle |
| 3 | Twitter Airline Sentiment | Airline tweet classification | ⭐⭐ | Kaggle |
| 4 | Amazon Reviews | Multi-class sentiment | ⭐⭐ | Kaggle |
| 5 | Fake News | Real vs fake articles | ⭐⭐ | Kaggle |
| 6 | AG News | 4-topic news classification | ⭐⭐ | Hugging Face |
| 7 | Quora Question Pairs | Semantic equivalence detection | ⭐⭐⭐ | Kaggle |
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | MNIST | Handwritten digit classification | ⭐ | Yann LeCun |
| 2 | Fashion-MNIST | Clothing category classification | ⭐ | GitHub |
| 3 | CIFAR-10 | 10-class image classification | ⭐⭐ | Official |
| 4 | Dogs vs Cats | Binary image classification | ⭐⭐ | Kaggle |
| 5 | Flowers Recognition | 5 flower categories | ⭐ | Kaggle |
| 6 | Intel Image Classification | 6 natural scene categories | ⭐⭐ | Kaggle |
| 7 | Chest X-Ray Pneumonia | Pneumonia detection | ⭐⭐ | Kaggle |
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | Mall Customers | Customer segmentation | ⭐ | Kaggle |
| 2 | Credit Card Segmentation | Spending behavior clusters | ⭐⭐ | Kaggle |
| 3 | Wholesale Customers | Distributor spending data | ⭐ | UCI |
| 4 | World Happiness Report | Country happiness scores | ⭐ | Kaggle |
| 5 | Online Retail | Market basket analysis | ⭐⭐ | UCI |
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | Air Passengers | Monthly airline counts (1949–1960) | ⭐ | GitHub |
| 2 | Stock Market Data | Historical stock prices | ⭐⭐ | Kaggle |
| 3 | COVID-19 (JHU) | Global case tracking | ⭐ | GitHub |
| 4 | Energy Consumption | Hourly power data (LSTM-ready) | ⭐⭐ | Kaggle |
| 5 | Jena Climate | 420K hourly weather readings | ⭐⭐⭐ | TensorFlow |
| # | Dataset | Description | Level | Download |
|---|---|---|---|---|
| 1 | MovieLens (ml-100k) | 100K movie ratings | ⭐ | GroupLens |
| 2 | Book-Crossing | 270K+ book ratings | ⭐⭐ | Kaggle |
| 3 | Amazon Product Ratings | Cross-category ratings | ⭐⭐ | UCSD |
| 4 | Jester Jokes | 73K user joke ratings | ⭐⭐ | UC Berkeley |
| Platform | Description | Link |
|---|---|---|
| Kaggle | Largest dataset community + competitions | kaggle.com/datasets |
| UCI ML Repository | Classic academic datasets | archive.ics.uci.edu |
| Google Dataset Search | Public dataset search engine | datasetsearch.research.google.com |
| Hugging Face | NLP datasets hub | huggingface.co/datasets |
| Papers With Code | Research-linked datasets | paperswithcode.com/datasets |
| data.gov | U.S. government open data | data.gov |
| OpenML | AutoML datasets | openml.org |
💡 Beginner tip: Start with Iris, Titanic, or MNIST — each teaches a complete ML workflow in under 100 lines of code!
| 🧠 Healthcare | 💬 NLP & Chatbots | 📈 Forecasting |
| Alzheimer's Predictor | Chatbot Using RASA | COVID-19 Prophet Forecast |
| Brain Tumor Detection | Fake News Detection | Crude Oil Forecasting |
| Heart Disease Prediction | Emotion Recognition NLP | Covid Third Wave Forecast |
| 👁️ Computer Vision | 🤖 Deep Learning | 🏦 Finance & Business |
| Eye Gaze Tracking | ANN from Scratch | Portuguese Bank Marketing |
| Deepfake Image Analyzer | Bidirectional LSTM | Bitcoin Price Predictor |
| Chicken Disease Classification | Weapon Detection System | Customer Segmentation |
| # | Project | Description |
|---|---|---|
| 1 | Alzheimer's Disease Predictor | ML model predicting Alzheimer's likelihood using classification & feature selection |
| 2 | Chatbot Using RASA | Conversational AI handling diverse user queries |
| 3 | COVID-19 Forecasting with Prophet | Time-series forecasting of case trends |
| 4 | Fake News Detection | NLP-based fake news classification |
| 5 | Eye Gaze Tracking & Attention Estimation | Real-time attention tracking with MediaPipe & 3D head pose estimation |
| 6 | Portuguese Bank Marketing | Binary classification for term deposit subscription |
📋 Quick Project Index — Click to expand full list
📌 & many more... Explore the full repository for 500+ additional projects!
🟢 Beginner & Data Analysis
| Project | Category | Level | Link |
|---|---|---|---|
| Anime Data Analysis | Data Analysis | Beginner | View → |
| Medical Cost Prediction | ML | Beginner | View → |
| Heart Disease Detection | ML | Beginner | View → |
| Water Potability | ML | Intermediate | View → |
🔵 Deep Learning & Computer Vision
| Project | Category | Level | Link |
|---|---|---|---|
| Alzheimer's Predictor | Deep Learning | Intermediate | View → |
| Yoga Pose Detection | Computer Vision | Intermediate | View → |
| Speech-to-Image Generator | Deep Learning | Advanced | View → |
| Weapon Detection System | Computer Vision | Advanced | View → |
🟡 NLP & Advanced ML
| Project | Category | Level | Link |
|---|---|---|---|
| Toxic Comment Classifier | NLP | Intermediate | View → |
| Currency Arbitrage with RL | Reinforcement Learning | Advanced | View → |
| Sales Prediction (Research) | ML | Advanced | View → |
| Resource | Link |
|---|---|
| 8 Basic Statistics Concepts | KDnuggets |
| Machine Learning with Python (Coursera) | Coursera |
| Python ML Getting Started (W3Schools) | W3Schools |
| ML with Python (freeCodeCamp) | freeCodeCamp |
# 1. Fork & clone the repository
git clone https://github.com/Niketkumardheeryan/ML-CaPsule.git
cd ML-CaPsule
# 2. Create a feature branch
git checkout -b my-feature
# 3. Pick a project folder and start learning!
We welcome contributions from everyone! Here's how to get involved:
| Step | Action | Link |
|---|---|---|
| 1 | Read contribution guidelines | CONTRIBUTING.md |
| 2 | Browse existing issues | Issues |
| 3 | Submit a pull request | Pull Requests |
# Fork → Clone → Branch → Commit → Push → PR
git clone https://github.com/YOUR_USERNAME/ML-CaPsule.git
cd ML-CaPsule
git checkout -b my-feature
# Make your changes
git add .
git commit -m "Add: descriptive message about your change"
git push origin my-featureThen open a Pull Request on GitHub with a clear description of your changes.
ML-CaPsule/
├── 📂 Project folders/ # 500+ individual ML projects
├── 📄 CONTRIBUTING.md # Contribution guidelines
├── 📄 CODE_OF_CONDUCT.md # Community standards
└── 📄 LICENSE # MIT License
Please read our Code of Conduct before contributing.
Thanks to all these amazing people who made ML-CaPsule possible! 🎉
 Niket Kumar Dheeryan Author 💻 |
 Abhishek Sharma 💻 |
 Sakalya100 💻 |
 Kaustav Roy 💻 |
 Soumayan Pal 💻 |
 Komal Gupta 💻 |
 Manu Varghese 💻 |
 Abhishek Panigrahi 💻 |
 Padmini Rai 💻 |
 psyduck1203 💻 |
 Rutik Bhoyar 💻 |
 Ayushi Shrivastava 💻 |
This project is licensed under the MIT License.
Feel free to create issues, fix bugs, and contribute. Join our community!
Built with ❤️ by Niketkumardheeryan and contributors