Welcome to the Machine Learning Algorithms from Scratch repository! 🚀 In this project, I implement foundational machine learning algorithms entirely from scratch using Python 🐍. The goal is to deepen understanding of how these algorithms work under the hood.
Here are the algorithms implemented so far:
- 🔍 K-Nearest Neighbors (KNN)
- 🌳 Decision Tree
- 📈 Linear Regression
- 🤖 Perceptron
- 📊 More coming soon... stay tuned! 🛠️
This repository is built with simplicity in mind. It uses:
- Python (Core programming)
- NumPy (For efficient numerical computations) ⚡
No pre-built ML libraries like Scikit-learn are used—because we’re doing it from scratch! 🛡️
Understanding the fundamentals of machine learning algorithms is crucial for:
- 📖 Gaining deep insights into their workings
- 🛠️ Debugging complex models
- 🎯 Optimizing performance
- 🚪 Opening doors to advanced topics like model customization
🌟 Star this repository if you find it helpful! ⭐
💬 Feel free to open issues for any bugs or suggestions. Let's learn and grow together! 😊