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Introduction to Linear Algebra (Indian Edition)

- ➔ Table of Contents
- ➔ Index
- ➔ Matrix Factorizations
- ➔ Six Great Theorems/

Linear Algebra in a Nutshell - ➔ Singular Value Decomposition of Real Matrices

Prof. Jugal K. Verma, IIT Bombay (March 2020) - ➔ Book sections and resources
- ➔ Review by Douglas Farenick, University of Regina
- ➔ Review by George Cobb, Mount Holyoke College

Linear Algebra and Learning from Data (Indian Edition)

- ➔ Table of Contents
- ➔ Preface
- ➔ The Functions of Deep Learning
- ➔ Deep Learning & Neural Nets
- ➔ Counting Parameters in the Basic Factorizations
- ➔ Matrix derivatives by Dan Drucker :

Proof that*A*is the closest rank_{k}*k*matrix to*A* - ➔ The Central Limit Theorem (page 288)
- ➔ Book sections and resources
- ➔
*SIAM Review*(2020)

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Gilbert Strang @ MITGilbert Strang @ OpenCourseWare

Gilbert Strang @ Wikipedia

Web page dedicated to 'Introduction to Linear Algebra' (MIT course 18.06)

Web page dedicated to 'Linear Algebra and Learning from Data' (MIT course 18.065)

Explore & Build : Neural Networks and Deep Learning

Gil Strang is still going strong, online and in print (May 8, 2019)

Lectures, Interviews

A 2020 Vision of Linear Algebra, Spring 2020 (OpenCourseWare)

18.06 Introduction to Linear Algebra (OpenCourseWare)

18.06 Linear Algebra, Spring 2005 (YouTube)

18.06 Introduction to Linear Algebra (OpenCourseWare)

18.06 Linear Algebra, Spring 2005 (YouTube)

18.06S Linear Algebra, Fall 2011 (YouTube)

MIT-18.065 Linear Algebra and Learning from Data (Spring, 2019)

18.065 Linear Algebra and Learning from Data (OpenCourseWare)

18.065 Introduction to Linear Algebra and Learning from Data (YouTube)

MIT-18.065 Linear Algebra and Learning from Data (Spring, 2019)

18.065 Linear Algebra and Learning from Data (OpenCourseWare)

18.065 Introduction to Linear Algebra and Learning from Data (YouTube)

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