Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
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Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)
Stavka #: 18006456

Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)

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Stavka #: 18006456

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Get an introduction to deep learning with Adaptive Computation and Machine Learning: Deep Learning Hardcover. Explore mathematical and conceptual background, industry techniques, research perspectives, and practical applications. Ideal for students, engineers, and researchers. Shop at Ubuy Croatia
  • 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.
Book formatHardcover
Fiction/nonfictionNon-Fiction
GenreComputing & Internet
Publication dateNovember, 2016
Pages800
Reading levelProfessional & Vocational, 18
Age range18 Years & Up
SubgenreArtificial Intelligence
Series titleAdaptive Computation and Machine Learning
Edition1
PublisherMIT Press
Original languagesEnglish
LanguageEnglish
Edu focusTechnology
Awards wonNone
Is collectibleN
EditorFrancis Bach
Binding typeCase Binding
Retail packagingSingle Piece
Assembled product height9.1 in
Assembled product weight2.8 lb (1.27 kg)
Bisac subject headingComputers
Package Weight2.6 Pound

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Adaptive Computation and Machine Learnin Deep Learning, (Hardcover)

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Naručite sada i dobijte ga oko Sunday, Listopad 11

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