Probabilistic ML - Lecture 10 - GP Regression: An Extensive Example
Channel: Tübingen Machine Learning
Date: 2023-05-26

This is the tenth lecture in the Probabilistic ML class of Prof. Dr. Philipp Hennig in the Summer Term 2023 at the University of Tübingen. 

Contents: 
* Gaussian Process Regression in practice
* Kernel choice and design
* hyperparameter adaptation by type-II Maximum Likelihood / Evidence Maximization
* Source Separation

The slides for this course are available at https://github.com/philipphennig/Probabilistic_ML

© Philipp Hennig / University of Tübingen, 2023 CC BY-NC-SA 4.0