LM101-079: Ch1: How to View Learning as Risk Minimization 474x50

This particular podcast covers the material in Chapter 1 of my new (unpublished) book...

This particular podcast covers the material in Chapter 1 of my new (unpublished) book “Statistical Machine Learning: A unified framework”. In this episode we discuss Chapter 1 of my new book, which shows how supervised, unsupervised, and reinforcement learning algorithms can be viewed as special cases of a general empirical risk minimization framework. This is useful because it provides a framework for not only understanding existing algorithms but also for suggesting new algorithms for specific applications.

LM101-080: Ch2: How to Represent Knowledge using Set Theory +1 año 31:42 LM101-081: Ch3: How to Define Machine Learning (or at Least Try) +1 año 37:19 LM1010-082: Ch4: How to Analyze and Design Linear Machines +1 año 29:04 LM101-083: Ch5: How to Use Calculus to Design Learning Machines +1 año 34:21 LM101-084: Ch6: How to Analyze the Behavior of Smart Dynamical Systems +1 año 33:12 Ver más en APP Comentarios del episodio 483258