This is a collection of my projects and lecture notes, designed to enhance learning and solidify my understanding of convex optimization concepts crucial for mastering Machine Learning and Data Science.

Convex Analysis

Optimization Algorithms

Gradient Methods

Newton Methods

In this project, we will delve into a variety of optimization algorithms frequently utilized in the field of operations research. These include, but are not limited to, the Simplex Method, Alternating Direction Methods of Multipliers (ADMM), Gradient Descent, and Newton’s Methods among others.

The implementation of this project is available here.