Linear Algebra and Optimization with Applications to Machine Learning - Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning

Gallier, Jean H; Quaintance, Jocelyn

ISBN 10: 9811206392 / ISBN 13: 9789811206399

Published by World Scientific Pub Co Inc, 2020

About this Item

This is a pre-loved book that shows moderate signs of wear from previous reading. You may notice creases, edge wear, or a cracked spine, but it remains in solid, readable condition.Please note:-May include library or rental stickers, stamps, or markings.-Supplemental materials e.g., CDs, access codes, inserts are not guaranteed.-Box sets may not come with the original outer box. If it does, the box will not be in perfect condition. -Sourced from donation centers; authenticity not verified with publisher. Your satisfaction is our top priority! If you have any questions or concerns about your order, please donā t hesitate to reach out. Thank you for shopping with us and supporting small businessā happy reading!

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Bibliographic Details

• Title: Linear Algebra and Optimization with Applications to Machine Learning - Volume I: Linear Algebra for Computer Vision, Robotics, and Machine Learning
• Publisher: World Scientific Pub Co Inc
• Publication Date: 2020
• Language: English
• ISBN 10: 9811206392
• ISBN 13: 9789811206399
• Binding: Hardcover
• Condition: good

About this title

Synopsis

This book provides the mathematical fundamentals of linear algebra to practicers in computer vision, machine learning, robotics, applied mathematics, and electrical engineering. By only assuming a knowledge of calculus, the authors develop, in a rigorous yet down to earth manner, the mathematical theory behind concepts such as: vectors spaces, bases, linear maps, duality, Hermitian spaces, the spectral theorems, SVD, and the primary decomposition theorem. At all times, pertinent real-world applications are provided. This book includes the mathematical explanations for the tools used which we believe that is adequate for computer scientists, engineers and mathematicians who really want to do serious research and make significant contributions in their respective fields.