PhD Course: Introduction to Machine Learning

by Bryan Zaldivar (CSIC IFIC)

Monday 19 May 2025, 11:00 → Friday 30 May 2025, 13:00 Europe/Madrid

1001-Primera-1-1-1 - Paterna. Seminario (Universe)

This course will be mostly blackboard-based, focusing on the statistical foundations of Machine Learning. Many numerical examples will be given in python notebooks, for the sake of illustration and further usefulness to the attendees, and two hands-on sessions are conceived. The required background to make the most of these lectures is, on the one hand, a good level of linear algebra, as well as familiarity with concepts of statistics (probability distributions, likelihood, Bayes theorem, etc)

Preliminary outline (it may change to some extent):

lecture 1: review of ML + summary of statistics -- May 19th (Mon.), 11:00-13:00

lecture 2: regression and overfitting control -- May 21th (Wed.), 11:00-13:00

lecture 3: bayesian learning  -- May 21th (Wed.), 15:00-17:00

lecture 4: classification -- May 22th (Thu.), 11:00-13:00

lecture 5 (hands-on session): classification  -- May 23th (Fri.), 11:00-13:00

lecture 6: neural networks  -- May 26th (Mon.), 11:00-13:00

lecture 7 (hands-on session): neural nets  -- May 27th (Tue.), 15:00-17:00

lecture 8: non-parametric methods  -- May 28th (Wed.), 11:00-13:00

lecture 9: gaussian processes  -- May 29th (Thu.), 11:00-13:00

lecture 10: unsupervised learning  -- May 30th (Fri.), 11:00-13:00