Deep Learning [Audiobook] download free by Yoshua Bengio

Deep Learning Audiobook download free by Yoshua Bengio
  • Listen audiobook: Deep Learning
  • Author: Yoshua Bengio
  • Release date: 2017/6/2
  • Publisher: MIT PRESS LTD
  • Language: English
  • Genre or Collection: Society and Social Sciences
  • ISBN: 9780262035613
  • Rating: 7.52 of 10
  • Votes: 338
  • Review by: Maddux Siegel
  • Review rating: 8.73 of 10
  • Review Date: 2018/10/21
  • Duration: 9H53M26S in 256 kbps (160 MB)
  • Date of creation of the audiobook: 2018-08-23
  • You can listen to this audiobook in formats: MOD, Musepack, WAV, MP3, FLAC, WMA, MPEG4 (compression CBZ, ARJ, ZIP, TBZ, RAR, ISO)
  • Total pages original book: 800
  • Includes a PDF summary of 73 pages
  • Duration of the summary (audio): 53M7S (14.6 MB)
  • Description or summary of the audiobook: 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 SpaceXDeep 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.
  • Other categories, genre or collection: Machine Learning, Neural Networks & Fuzzy Systems, Teaching Resources & Education, Computer Science, Artificial Intelligence
  • Download servers: Microsoft OneDrive, BitShare, Hotfile, FileServe, MEGA, ShareByLink, Novafile. Compressed in CBZ, ARJ, ZIP, TBZ, RAR, ISO
  • Format: Hardback
  • Approximate value: 90.36 USD
  • Dimensions: 178x229x32mm
  • Weight: 1,270.06g
  • Printed by: MIT Press
  • Published in: Cambridge, Mass., United States

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