LM101-083: Ch5: How to Use Calculus to Design Learning Machines

This particular podcast covers the material from Chapter 5 of my new book “Statistical Machine Learning: A unified framework” which is now available! The book chapter shows how matrix calculus is very useful for the analysis and design of both linear and nonlinear learning machines with lots of examples. We discuss the relevance of the matrix chain rule and matrix Taylor series for machine learning algorithm design and the analysis of generalization performance! Check out: www.learningmachines101.com