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University of California, Davis

Linear Algebra for Machine Learning

University of California, Davis via edX

Overview

This course gives you an introduction to some key ideas in Linear algebra and how these ideas are used in applications related to Machine Learning. You’ll learn about some fundamental objects in linear algebra – vectors and matrices – and how these are used to represent data. Together with operations on vectors and matrices, we get a number of applications including predictive models of data, dimensionality reduction strategies, and recommendation systems.

This course offers a foundation in a topic central to the world of machine learning and artificial intelligence. Upon completion, you will be able to further explore topics of interest expressed in the language of vectors and matrices.

Taught by

Jacob Koehler

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