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

Learning Machines 101 - A podcast by Richard M. Golden, Ph.D., M.S.E.E., B.S.E.E.

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This particular podcast covers the material in Chapter 1 of my new (unpublished) book “Statistical Machine Learning: A unified framework”.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 for suggesting new algorithms for specific applications

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