This repository was created for study purposes as part of the D603 Machine Learning course. It contains from-scratch implementations of various machine learning algorithms covered in the class.

The goal of this project is to deepen understanding by manually building each algorithm, alongside equivalent Jupyter notebooks that demonstrate how the same models are used with standard Python libraries (e.g., scikit-learn, NumPy, Pandas, etc.).

• Pure Python implementations of core machine learning algorithms
• Jupyter notebooks with library-based equivalents
• Example datasets used for demonstration and testing
• Exploratory analysis and result comparisons

This project is intended for educational and informational purposes only.