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

Jean Gallier, Jocelyn Quaintance

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商品描述

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.

商品描述(中文翻譯)

本書向在計算機視覺、機器學習、機器人學、應用數學和電氣工程等領域從事實踐的人提供了線性代數的數學基礎。作者們僅假設讀者具備微積分知識,以嚴謹而平易近人的方式,發展了概念背後的數學理論,如:向量空間、基底、線性映射、對偶性、酉空間、譜定理、奇異值分解和主要分解定理。同時,書中提供了相關的實際應用。本書包含了工具的數學解釋,我們相信這對於真正想在自己的領域進行深入研究並做出重要貢獻的計算機科學家、工程師和數學家來說是足夠的。