"Less magic. More intuition."
Welcome! 👋
This repository is my public journey of learning Machine Learning from first principles. Instead of treating algorithms as black boxes, I'm diving deep into the mathematics, intuition, implementation, and practical applications behind each one.
Every topic includes:
- 📖 Intuition and mathematical foundations
- 🛠️ Implementation from scratch using NumPy/Python
- 🤖 Implementation using scikit-learn (or relevant libraries)
- 📊 Visualizations and experiments
- ✍️ A detailed Medium article explaining the concept
Whether you're a beginner, preparing for interviews, or simply curious about how ML works under the hood, I hope this repository helps you learn along with me.
- Understand the mathematics behind every algorithm
- Build each algorithm from scratch
- Compare custom implementations with popular libraries
- Develop intuition instead of memorizing formulas
- Share everything through well-documented code and articles
There are countless tutorials that show how to use machine learning libraries.
This repository focuses on understanding why they work.
The goal isn't just to train models—it's to build intuition that lasts.
Found a mistake? Have a better explanation? Want to improve an implementation?
Feel free to open an Issue or submit a Pull Request.
Learning is always better together.
If you find this repository helpful:
- ⭐ Star the repository
- 🍴 Fork it
- ✍️ Read and share the accompanying Medium articles
- 💬 Share your feedback
I'll be publishing a Medium article alongside every major algorithm.
- 💼 LinkedIn: https://www.linkedin.com/in/rajiv-gupta99/
- 🌐 Portfolio: https://www.datascienceportfol.io/rajivgupta
- ✍️ Medium: Coming Soon
Stay tuned! 🚀
"The best way to truly understand an algorithm is to build it yourself."