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Deep Learning (Adaptive Computation and Machine Learning series)
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（4092）
US $67.89
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估計於 12月2日 (星期二)至 12月8日 (星期一)之間送達 運送地點 94104
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- 物品狀況
- 全新: 全新，未閱讀過和使用過的書籍，狀況完好，不存在缺頁或內頁受損。 查看所有物品狀況定義會在新視窗或分頁中開啟
- Brand
- MIT Press
- ISBN
- 0262035618
- ISBN10
- 0262035618
- ISBN13
- 9780262035613
- EAN
- 9780262035613
- GTIN
- 09780262035613
- MPN
- does not apply
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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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- n***1 (28)- 買家留下的信用評價。過去 6 個月購買已獲認證The book is new and sealed as described, there is a slight dint on one of the corners but it's fairly minor and acceptable at the low price I paid. The item was packed and shipped within an hour of being purchased and arrived fairly quickly. The book was securely packed and wrapped in plenty of bubble wrap. I am happy with my purchase.Justice League Dark: Rebirth Omnibus（#326370869142）
- 2***i (31)- 買家留下的信用評價。過去 1 個月購買已獲認證Fast shipping. Packaging better than some; makes in bubble wrap envelope. Item arrived basically as described. Binding a loose for a book labeled new. Quality ok for the price. If price was right would order from seller again.
- e***e (129)- 買家留下的信用評價。過去 1 個月購買已獲認證Most improved shipper! I buy comic omnis (big heavy books). The first time I bought from them many months ago, it was just in a mailer and damaged. The last couple of orders have been very well packaged tightly in shrink wrap and snug inside an appropriately sized box. Shipping was also swift. They're fast becoming a favorite ebayer!