Linear Algebra and Learning from Data > 수학/통계학

Table of Contents

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;

Index of authors;

Index;

Index of symbols.