- 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.
Credits Gautam-J/Machine-Learning