Numerics of Machine Learning

Information

• Lecturer: N. Bosch, J. Grosse, P. Hennig, A. Kristiadi, M. Pförtner, J. Schmidt, L. Tatzel, F. Schneider, J. Wenger
• Semester: Winter 2022
• Website: https://github.com/philipphennig/NumericsOfML
• Slides: https://github.com/philipphennig/NumericsOfML/tree/main/slides
• Video: https://www.youtube.com/playlist?list=PL05umP7R6ij2lwDdj7IkuHoP9vHlEcH0s

Summary

This class discusses both practical and theoretically interesting aspects of the algorithms that drive machine learning. It endorses the view of Probabilistic Numerics, the idea that computation itself is an inference process, to describe the numerical algorithms inside the learning machine, as learning machines.

Cite this Course

@techreport{NoML22,
   title       = {Numerics of Machine Learning},
   author      = {N. Bosch and J. Grosse and P. Hennig and A. Kristiadi and M. Pförtner 
                  and J. Schmidt and F. Schneider and L. Tatzel and J. Wenger},     
   series      = {Lecture Notes in Machine Learning},     
   year        = {2022},
   institution = {Tübingen AI Center},
}