SamirMoustafa / Machine-Learning-Implementation

Naive implementation for Machine Learning algorithms

Machine Learning Implementation from Scratch

This repo design to be a reference for me to review machine learning basics algorithms

Content

• K-Nearest Neighbors
• K-Mean
• ID3 (Decision Tree)
• CART (Decision Tree)
• Random Forest (Decision Tree)

Requirements

• Python 3.5+
• Jupyter notebook
• NumPy
• Pandas
• Matplotlib
• Scipy

Data-set

Every algorithm use different dataset that's generated from Numpy or loaded from CSV file.

Research

Please use this bibtex if you want to cite this repository in your publications:

@misc{Machine Learning,
    author = {Samir Moustafa},
    title = {Machine Learning Implementation from Scratch},
    year = {2019},
    publisher = {GitHub},
    journal = {GitHub repository},
    howpublished = {https://github.com/SamirMoustafa/Machine-Learning-Implementation}
}