Machine Learning Models from scratch

This repository contains Jupyter Notebooks with implementations of different ML models. For every Model there is an example with sklearn and an implementation from scratch.

At the top of each Notebook I linked the sources I used. My main source is sentdex's machine learning tutorial. The "example"-notebooks contain a brief explaination of the model used. In (almost) every "from-scratch"-Notebook I wrote an explaination of the model & code.

List of ML models that have been implemented:

• Linear regression
• K nearest neighbors
• Support vector machine
• Decision Tree
• Random Forest
• K Means
• Mean shift

Installation Instructions

• Please install Python on your machine: https://realpython.com/installing-python/

• Install pip if not already installed: https://pip.pypa.io/en/stable/installing/

• Install git on your machine: https://www.atlassian.com/git/tutorials/install-git

• Open terminal in your machine and clone this repository:

git clone https://github.com/chagri/Machine-Learning-From-Scratch.git

• Once cloned enter the repository:

cd Machine-Learning-From-Scratch

• Install requirements:

pip install -r requirements.txt

• Once installed, start Jupyter notebook server, which will give you a url where you can start playing with the code:

jupyter notebook