Introduction to Machine Learning and Deep Learning

This set of pages is written with the objective of providing a quick introductory base of knowledge about Machine Learning (ML) and Deep Learning (DL). I specifically write these pages so that my undergraduate or master students understand most of the materials presented in my lab sessions or the papers used in our research projects better.

Of course, these cannot be counted as a comprehensive source in the discussed subjects, but they are a good starting point for delving into the materials.

We are engineers, and the spirit of these writings is to provide a just “what-is-needed-to-know?” type of source with the objective of using the materials in a given engineering application. So, I will just state the things which are needed.

• Basics of Linear Algebra: In This page we talk about basic concepts and operations from Linear Algebra which are widely used in ML and DL applications. If you have passed classes in linear algebra or linear programming you may skip this section.