Linear Algebra and Learning from Data ISBN13：9780692196380 出版社：Cambridge Univ Pr 作者：Gilbert Strang 裝訂：精裝 出版日：2019/02/28 內容簡介 ●The first textbook designed to teach linear algebra as a tool for deep learning ●From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra ●Includes the necessary background from statistics and optimization ●Explains stochastic gradient descent, the key algorithim of deep learning, in detail 目錄 Deep learning and neural nets Preface and acknowledgements Part I. Highlights of Linear Algebra Part II. Computations with Large Matrices Part III. Low Rank and Compressed Sensing Part IV. Special Matrices Part V. Probability and Statistics Part VI. Optimization Part VII. Learning from Data Books on machine learning Eigenvalues and singular values: Rank One Codes and algorithms for numerical linear algebra Counting parameters in the basic factorizations