Hands On Mathematics For Deep Learning

Download Hands On Mathematics For Deep Learning full books in PDF, epub, and Kindle. Read online free Hands On Mathematics For Deep Learning ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!


Related Books

Hands-On Mathematics for Deep Learning
Language: en
Pages: 347
Authors: Jay Dawani
Categories: Computers
Type: BOOK - Published: 2020-06-12 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

A comprehensive guide to getting well-versed with the mathematical techniques for building modern deep learning architectures Key FeaturesUnderstand linear alge
Hands-On Mathematics for Deep Learning
Language: en
Pages: 364
Authors: Jay Dawani
Categories: Computers
Type: BOOK - Published: 2020-06-12 - Publisher:

DOWNLOAD EBOOK

The main aim of this book is to make the advanced mathematical background accessible to someone with a programming background. This book will equip the readers
Mathematics for Machine Learning
Language: en
Pages: 392
Authors: Marc Peter Deisenroth
Categories: Computers
Type: BOOK - Published: 2020-04-23 - Publisher: Cambridge University Press

DOWNLOAD EBOOK

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, opti
Hands-On Deep Learning Algorithms with Python
Language: en
Pages: 498
Authors: Sudharsan Ravichandiran
Categories: Computers
Type: BOOK - Published: 2019-07-25 - Publisher: Packt Publishing Ltd

DOWNLOAD EBOOK

Understand basic to advanced deep learning algorithms, the mathematical principles behind them, and their practical applications. Key FeaturesGet up-to-speed wi
Math for Deep Learning
Language: en
Pages: 346
Authors: Ronald T. Kneusel
Categories: Computers
Type: BOOK - Published: 2021-12-07 - Publisher: No Starch Press

DOWNLOAD EBOOK

Math for Deep Learning provides the essential math you need to understand deep learning discussions, explore more complex implementations, and better use the de