Linear regression with Gradient Descent

About The Project

To better understand the gradient descent algorithm, I've tried to implement it from scratch for a simple problem : linear regression.

I've implemented :

• Classic GD
• SGD
• Mini-batch SGD

Prerequisites

• Python ⩾ 3.8

  sudo apt install python3 python3-pip

Installation

1. Clone the repo

   git clone https://github.com/Clement-W/Linear-Regression-SGD.git
   cd Linear-Regression-SGD/

2. Create and activate a virtual environment

   pip3 install virtualenv --upgrade
   virtualenv venv
   source venv/bin/activate

3. Install the requirements

   pip3 install -r requirements.txt

Demo

To see a demo, check the notebook file "LinearRegression_GD.ipynb". You'll find multiple examples of linear regression with classic gradient descent, stochastic gradient descent and mini batch stochastic gradient descent.

Contributing

I'm still learning machine learning, so feel free to use Issues or PR to report errors and/or propose additions or corrections to my code.