Optimization and Machine Learning

In this two-day course, we will cover:

1. the basics of unconstrained optimization and the connection to the training of machine learning models. 
2. The (global) optimization with data-driven models embedded. We focus on artificial neural networks and Gaussian processes. 

The course will use the flipped classroom format. Pre-recorded videos (from or own Massive Online Open Course as well as selected public videos) will be made available beforehand, with sufficient time allocated for self-studying, and then revised and discussed in an interactive live session. To reinforce the material taught, hands-on exercises using Jupyter notebooks will conclude each session. Each participant is asked to bring their own laptop to the course. 

Attached, you find a preliminary schedule. Note that, although the first sessions start at 10:00am, you may arrive as early as 8:00am and use the time for self-studying. The study material will be shared in the week before the course.