
Linear Algebra for AI - Generative AI
Master Linear Algebra: Essential Math for AI , Data Science, Machine Learning, and Deep Learning Applications
Taught by Professor Francis Su of Harvey Mudd College, this course covers the topics of a first-semester college course in linear algebra, including vector spaces, dot and cross products, matrix operations, linear transformations, determinants, eigenvectors and eigenvalues, and much more. Professor Su introduces many fascinating applications of linear algebra, from computer graphics to quantum mechanics.
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Master Linear Algebra: Essential Math for AI , Data Science, Machine Learning, and Deep Learning Applications
Linear Algebra for Data Science, Big Data, Machine Learning, Engineering & Computer Science. Master Linear Algebra
Learn concepts in linear algebra and matrix analysis, and implement them in MATLAB and Python.
Explore some fascinating applications of both linear algebra and statistics with this two-course set. In Mastering Linear Algebra: An Introduction with Applications, discover the ideal starting point for approaching the influential branch of mathematics in which algebra meets geometry. And in Learning Statistics: Concepts and Applications in R, discover how to apply elementary statistical methods in a free, open-source computer language used by millions of people around the world.
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