ML-lectures | Here is the material for a course of two-weeks I will be

ML-lectures is a Jupyter Notebook library. ML-lectures has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

The lectures are devoted to students having little knowledge of python, but being aware of linear algebra and basic calculus. The theaching philosophy is the following. I prefered to give a short theoretical introduction, then share practical code implementations and give students a sense of the “whole game” before delving into lower-level details. Theory is really important to become a self-confident and solid data scientist, but to start and to not get scared I was looking for a compromise between a complete bottom-up approach and the first principle derivation. I am really eager to get your comments and suggestions, so please do not be shy and tell me what you think and where I can improve.