Linear Algebra and Learning from Data

This book PDF is perfect for those who love Computers genre, written by Gilbert Strang and published by Wellesley-Cambridge Press which was released on 31 January 2019 with total hardcover pages 446. You could read this book directly on your devices with pdf, epub and kindle format, check detail and related Linear Algebra and Learning from Data books below.

Linear Algebra and Learning from Data
Linear Algebra and Learning from Data
Author : Gilbert Strang
File Size : 48,9 Mb
Publisher : Wellesley-Cambridge Press
Language : English
Release Date : 31 January 2019
ISBN : 0692196382
Pages : 446 pages
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Linear Algebra and Learning from Data by Gilbert Strang Book PDF Summary

Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a complete course in the linear algebra and related mathematics that students need to know to get to grips with learning from data. Included are: the four fundamental subspaces, singular value decompositions, special matrices, large matrix computation techniques, compressed sensing, probability and statistics, optimization, the architecture of neural nets, stochastic gradient descent and backpropagation.

Linear Algebra and Learning from Data

Linear Algebra and Learning from Data by Gilbert Strang

Linear algebra and the foundations of deep learning, together at last! From Professor Gilbert Strang, acclaimed author of Introduction to Linear Algebra, comes Linear Algebra and Learning from Data, the first textbook that teaches linear algebra together with deep learning and neural nets. This readable yet rigorous textbook contains a

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