Aggarwal, Charu C.

Linear Algebra and - Optimization for Machine - Learning: A Textbook

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ISBN 13:: 9783030403461
author:: Aggarwal, Charu C.
format:: Paperback
publisher:: Springer
language:: English
Publication Year:: 2021
Pages:: 495
Dimensions:: 25.4 x 17.8 x 2.7 centimetres (0
Genre:: Professional & Vocational, Computers, Artificial Intelligence,
Condition:: New
Availability:: Item usually sent within 5 working days

£54.54

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Description

Description

Linear Algebra and Optimization for Machine Learning A Textbook by Charu C. Aggarwal provides a comprehensive introduction to linear algebra and optimization in the context of machine learning. This textbook is designed for graduate-level students and professors in computer science, mathematics, and data science, as well as advanced undergraduate students. The book focuses on the basics of linear algebra and their applications to machine learning, including singular value decomposition, matrix factorization, similarity matrices (kernel methods), and graph analysis. It also explores optimization and its applications in machine learning, including least-squares regression, support vector machines, logistic regression, and recommender systems. With numerous examples and exercises throughout the book, Linear Algebra and Optimization for Machine Learning A Textbook is an ideal resource for those looking to apply linear algebra concepts to real-world machine learning problems.

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