Deep Learning

Deep Learning
Author :
Publisher : MIT Press
Total Pages : 801
Release :
ISBN-10 : 9780262337373
ISBN-13 : 0262337371
Rating : 4/5 (371 Downloads)

Book Synopsis Deep Learning by : Ian Goodfellow

Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.


Deep Learning Related Books

Deep Learning
Language: en
Pages: 801
Authors: Ian Goodfellow
Categories: Computers
Type: BOOK - Published: 2016-11-10 - Publisher: MIT Press

GET EBOOK

An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and res
Suggestions to Medical Authors and A.M.A. Style Book
Language: en
Pages: 72
Authors: American Medical Association
Categories: Authorship
Type: BOOK - Published: 1919 - Publisher:

GET EBOOK

PUBLICATION MANUAL OF THE AMERICAN PSYCHOLOGICAL ASSOCIATION.
Language: en
Pages: 0
Authors: AMERICAN PSYCHOLOGICAL ASSOCIATION.
Categories:
Type: BOOK - Published: 2022 - Publisher:

GET EBOOK

Publication Manual of the American Psychological Association
Language: en
Pages: 428
Authors: American Psychological Association
Categories: Language Arts & Disciplines
Type: BOOK - Published: 2019-10 - Publisher: American Psychological Association (APA)

GET EBOOK

The Publication Manual of the American Psychological Association is the style manual of choice for writers, editors, students, and educators in the social and b
Introduction to Art: Design, Context, and Meaning
Language: en
Pages: 614
Authors: Pamela Sachant
Categories: Art
Type: BOOK - Published: 2023-11-27 - Publisher: Good Press

GET EBOOK

Introduction to Art: Design, Context, and Meaning offers a deep insight and comprehension of the world of Art. Contents: What is Art? The Structure of Art Signi