Machine learning and optimization theory is a repository of my theoretical course explaining the fundamentals of machine learning. Optimization theory, linear algebra, high-level calculus and differentiation are the building blocks of machine learning. In this course, I am trying to touch each of these to provide clear understanding about the idea lying behind machine learning. For that purpose, I prepared a presentation together with a coding session of human-brain age prediction by linear regression in JAX. This lecture is created to for 100TUNAI program initiated by BASIRA-CENTER.
- Part 1: Machine Learning and Optimization Theory
- Part 2: JAX Framework
- Part 3: Coding Session for Human-Brain Age Prediction
The presentation prepared for parts 1 and 2 are accessible in this repository as pdf format. The animations in the presentation do not work for its pdf version, so mac-keynote and pptx formats are also added into the drive folder together with colab and dataset files. For additional JAX tutorials, you can visit my kaggle notebooks. What the lecture focuses on is briefly illustrated in the following lecture sketch map:
