Machine Learning Programming: Introduction

This lecture introduces the Machine Learning Programming course, a pure programming course following the Applied Machine Learning course. It covers prerequisites in MATLAB programming and basics in Machine Learning, including Principal Component Analysis, K-nearest Neighbor, K-means, Gaussian Mixture Model, and Neural networks. The lecture also explains the grading scheme, the use of Virtual Machines for a working environment, and the use of EPFL MOODLE for course materials and assignments. Students are guided on using Discord for asking questions, working individually or in groups, and seeking assistance from teaching assistants.