ML Algorithms by Hand

This repository is a collection of core machine learning algorithms implemented from scratch in Python. The goal is to gain a deeper understanding of how these algorithms work under the hood, without relying on libraries like scikit-learn.

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📌 Overview

• Learn how ML algorithms work by coding them manually
• Great for students, researchers, and anyone curious about ML internals
• Compare hand-crafted algorithms with scikit-learn counterparts

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📁 Contents

• Simple_Linear_Regression.py: Manual implementation of linear regression
• scikit_learn_works.py: Comparison using scikit-learn
• requirements.txt: Dependencies

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🚀 Getting Started

1. Clone the repo

git clone https://github.com/hincaltopcuoglu/ML_Algorithms_by_Hand.git
cd ML_Algorithms_by_Hand

2. Create a virtual environment (optional but recommended)

python3 -m venv venv
source venv/bin/activate   # On Windows: venv\Scripts\activate

3. Install requirements

pip install -r requirements.txt

Run the Code

python Simple_Linear_Regression.py

🧠 Current Algorithms

✅ Simple Linear Regression
(More algorithms will be added in the future.)

🤝 Contributing

Contributions are welcome! If you’d like to:

Improve or refactor the code

Add new ML algorithms

Fix bugs or enhance documentation

Feel free to open a pull request or issue.

📄 License

This project is licensed under the MIT License — see the LICENSE file for details.