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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Ian Goodfellow is a Research Scientist at Google.
Yoshua Bengio is Professor of Computer Science at the Université de Montréal.
Aaron Courville is Assistant Professor of Computer Science at the Université de Montréal.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
Vendeur : ThriftBooks-Atlanta, AUSTELL, GA, Etats-Unis
Hardcover. Etat : Fair. No Jacket. Readable copy. Pages may have considerable notes/highlighting. ~ ThriftBooks: Read More, Spend Less. N° de réf. du vendeur G0262035618I5N00
Quantité disponible : 1 disponible(s)
Vendeur : World of Books (was SecondSale), Montgomery, IL, Etats-Unis
Hardback. Etat : Good. 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. N° de réf. du vendeur 00102043064
Quantité disponible : 13 disponible(s)
Vendeur : World of Books Inc, Montgomery, IL, Etats-Unis
Hardback. Etat : Good. 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. N° de réf. du vendeur CIN0262035618G
Quantité disponible : 13 disponible(s)
Vendeur : Goodwill Books, Hillsboro, OR, Etats-Unis
Etat : good. Signs of wear and consistent use. N° de réf. du vendeur 3IISI0000UDL_ns
Quantité disponible : 1 disponible(s)
Vendeur : Better World Books: West, Reno, NV, Etats-Unis
Etat : Very Good. Former library copy. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Includes library markings. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good. N° de réf. du vendeur 11546100-6
Quantité disponible : 1 disponible(s)
Vendeur : MendoncaBook, Slough, Royaume-Uni
Hardcover. Etat : Very Good. N° de réf. du vendeur 000760
Quantité disponible : 1 disponible(s)
Vendeur : BooksRun, Philadelphia, PA, Etats-Unis
Hardcover. Etat : Very Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting. N° de réf. du vendeur 0262035618-11-1
Quantité disponible : 4 disponible(s)
Vendeur : Textbooks and More, Atlanta, GA, Etats-Unis
Hardcover. Etat : Very Good. US trade hardcover. Very Good copy: binding tight and square, all pages present, covers and spine clean with no writing, marking, or inscriptions. Ships fast from Atlanta, GA in protective packaging. N° de réf. du vendeur 9780262035613
Quantité disponible : 1 disponible(s)
Vendeur : Kimmies Collection, Maryville, TN, Etats-Unis
hardcover. Etat : Very Good. a very nice copy! clean and tight pages. fast and secure shipping. N° de réf. du vendeur 73751
Quantité disponible : 1 disponible(s)
Vendeur : Swan Trading Company, GEORGETOWN, TX, Etats-Unis
hardcover. Etat : Very Good. Hardcover shows only light cover wear. Text is unmarked and binding tight. Ships FAST! N° de réf. du vendeur 2607200023
Quantité disponible : 1 disponible(s)