/summer-of-ml

This repository contains code and material for Summer of ML Day 2 session

Primary LanguageJupyter Notebook

Summer of ML 2021 - Day2

AIML Clue IIT Delhi

Topics Covered:

  • Introduction to ML
  • Multivariable Calculus - Gradient, Hessian, Jacobian
  • Gradient Descent Algorithm
  • Linear Regression

Credits: some of the material has been taken from Andrew Ng's CS229 course at Stanford University and the matrix calculus cookbook is taken from Petersen & Pedersen.

Visualization

Credits Gautam-J/Machine-Learning

Linear Regression

Gradient Descent