Lecture Notes for the paper written by Jeremy Howard (the 🐐) and Terence Parr on the essentials of matrix calculus for deep learning

Introduction

Review: Scalar derivative rules

Introduction to vector calculus and partial derivatives

Matrix Calculus

The gradient of neuron activation

The gradient of the neural network loss function

THE END :)