Lectures@PhysTH: Introduction to Machine Learning methods (1/4)

The main scope of these lectures is to provide the attendee with the basic mathematical/statistical knowledge to understand and use Machine Learning tools in her/his work. It is also conceived to be useful for practical implementations in Python language. The main focus will be on "Supervised Learning" techniques, considering both frequentist and Bayesian approaches. 
The format is mostly blackboard-based, while sometimes python codes will be shown. A  basic background on statistics would be benefitial from the attendees, although the lectures aim at starting at a very elementary level. 

Topic of Monday lectures:

 1. Overview of ML.   

2.  summary of statistics
 

The lectures will take place in Solvay Room at the 5th floor of the NO building (ULB, Campus Plaine).