Regression closed form and gradient descent Explained

This repository demonstrated the implementation of closed form and gradient descent techniques to solve regression problem in Python.

Introduction

Regression is one kind of supervised learning algorithm within machine learning family. It is an approach to model the relationship between the dependent variable, and explantory variables. Its objective is to predict a quantity of the target variable.

There are two main approaches to Linear Regression:

1. Solving model parameters analytically (closed form equation)
2. Using optimization algorithm (gradient descent, stochastic gradient descent, etc.)

Please refer to this jupyter notebook for the full implementation.