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Deep Learning (Adaptive Computation and Machine Learning series) Ian Goodfellow
US $67,49
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Prezzo iniziale: US $89,99 (25% di sconto)
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“This item is new and unused however due to lack of proper packaging there is a a small scuff on the ”... Maggiori informazioniinformazioni sulla condizione
Come Nuovo
Libro che sembra nuovo anche se è già stato letto. La copertina non presenta segni di usura visibili ed è inclusa la sovraccoperta(se applicabile) per le copertine rigide. Nessuna pagina mancante o danneggiata, piegata o strappata, nessuna sottolineatura/evidenziazione di testo né scritte ai margini. Potrebbe presentare minimi segni identificativi sulla copertina interna. Mostra piccolissimi segni di usura. Per maggiori dettagli e la descrizione di eventuali imperfezioni, consulta l'inserzione del venditore.
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Ritiro gratuito dell'oggetto in zona da Conway, Arkansas, Stati Uniti.
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Oggetto che si trova a: Conway, Arkansas, Stati Uniti
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Consegna prevista tra il ven 1 ago e il mer 6 ago a 94104
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Numero oggetto eBay:205317862213
Specifiche dell'oggetto
- Condizione
- Come Nuovo
- Note del venditore
- ISBN
- 9780262035613
Informazioni su questo prodotto
Product Identifiers
Publisher
MIT Press
ISBN-10
0262035618
ISBN-13
9780262035613
eBay Product ID (ePID)
228981524
Product Key Features
Number of Pages
800 Pages
Language
English
Publication Name
Deep Learning
Publication Year
2016
Subject
Intelligence (Ai) & Semantics, Computer Science
Type
Textbook
Subject Area
Computers
Series
Adaptive Computation and Machine Learning Ser.
Format
Hardcover
Dimensions
Item Height
1.3 in
Item Weight
45.5 Oz
Item Length
9.3 in
Item Width
7.3 in
Additional Product Features
Intended Audience
Trade
LCCN
2016-022992
Reviews
[T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology., [T]he AI bible... the text should be mandatory reading by all data scientists and machine learning practitioners to get a proper foothold in this rapidly growing area of next-gen technology.-- Daniel D. Gutierrez , insideBIGDATA --
Dewey Edition
23
Illustrated
Yes
Dewey Decimal
006.3/1
Synopsis
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., 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.
LC Classification Number
Q325.5.G66 2017
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- 3***r (24)- Feedback lasciato dall'acquirente.Ultimi 6 mesiAcquisto verificatoItem was exactly as described and arrived without any damage. I only gave four stars because I had messaged the seller after purchase with a question and never receive a response.
- e***_ (20)- Feedback lasciato dall'acquirente.Ultimi 6 mesiAcquisto verificatoItem is exactly as described and packed with much care. It arrived on time and I am very pleased with my purchase. I highly recommend seller and their fair, honest pricing.
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