The main focus of this particular episode covers the material in Chapter 4 of my new forthcoming book titled “Statistical Machine Learning: A unified framework.” Chapter 4 is titled “Linear Algebra for Machine Learning.
Many important and widely used machine learning algorithms may be interpreted as linear machines and this chapter shows how to use linear algebra to analyze and design such machines. In addition, these same techniques are fundamentally important for the development of techniques for the analysis and design of nonlinear machines.
This podcast provides a brief overview of Linear Algebra for Machine Learning for the general public as well as information
for students and instructors regarding the contents of Chapter 4
of Statistical Machine Learning. For more details, check out: www.statisticalmachinelearning.com
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