Extra Math for ML

Hi ! I am Pranav Joshi, at the time of writing this, a 2$^\text{nd}$ year C.S.E. Btech. student as IITGN. This is a collection of what I learnt from reading through the first 9 chapters of the book “Mathematics for Machine Learning”. I have tried to make these notes as to-the-point as possible.

Starters (preparation before going in)

There is certainly a bit of math that I assumed people who will read this would already know, and so, for completeness, I am linking my notes on those concepts (and more), as well. Enjoy !

3D coordinate geometry

Group Theory

Multivariable Calculus

Laplace Transform

SVD

Quadratic Forms

The main dish

Linear algebra

Analytic Geometry

Matrix Decompositions

Vector Calculus

Probability

Continuous Optimisation

Models as Graphs

Linear Regression