ML-Algorithms-From-Scratch

📌 About

This repository contains implementations of Machine Learning algorithms from scratch without using libraries like Scikit-Learn or TensorFlow. The goal is to understand the core mathematical concepts and how these algorithms work under the hood.

Additionally, this folder includes implementations using standard ML libraries for comparison and review.

📂 Contents

• Linear Regression - Implemented both from scratch and using Scikit-Learn.
• Logistic Regression- Implemented both from scratch and using Scikit-Learn
• More ML algorithms coming soon…

📚 Libraries Used

While the focus is on implementing ML algorithms manually, some versions also use:

• NumPy – For mathematical operations and array manipulations.
• Pandas – For handling datasets.
• Matplotlib & Seaborn – For data visualization.
• Scikit-Learn – For comparison with standard implementations.

🎯 Goals

✔ Understand ML algorithms at a deeper level.
✔ Improve coding and mathematical skills in ML.