|Eingestellt in Kategorie:
Ähnlichen Artikel verkaufen?

Deep Learning von Goodfellow, Ian NEU Hardcover

dunkin_bookstore
(36845)
Angemeldet als gewerblicher Verkäufer
US $134,71
Ca.CHF 106,57
Artikelzustand:
Neu
6 verfügbar
Ganz entspannt. Rückgaben akzeptiert.
Versand:
Kostenlos USPS Media MailTM.
Standort: Wayne, NJ, USA
Lieferung:
Lieferung zwischen Fr, 11. Jul und Do, 17. Jul bei heutigem Zahlungseingang
Liefertermine - wird in neuem Fenster oder Tab geöffnet berücksichtigen die Bearbeitungszeit des Verkäufers, die PLZ des Artikelstandorts und des Zielorts sowie den Annahmezeitpunkt und sind abhängig vom gewählten Versandservice und dem ZahlungseingangZahlungseingang - wird ein neuem Fenster oder Tab geöffnet. Insbesondere während saisonaler Spitzenzeiten können die Lieferzeiten abweichen.
Rücknahme:
30 Tage Rückgabe. Käufer zahlt Rückversand. Wenn Sie ein eBay-Versandetikett verwenden, werden die Kosten dafür von Ihrer Rückerstattung abgezogen.
Zahlungen:
     Diners Club

Sicher einkaufen

eBay-Käuferschutz
Geld zurück, wenn etwas mit diesem Artikel nicht stimmt. Mehr erfahreneBay-Käuferschutz - wird in neuem Fenster oder Tab geöffnet
Der Verkäufer ist für dieses Angebot verantwortlich.
eBay-Artikelnr.:235514964987
Zuletzt aktualisiert am 02. Jul. 2025 14:21:42 MESZAlle Änderungen ansehenAlle Änderungen ansehen

Artikelmerkmale

Artikelzustand
Neu: Neues, ungelesenes, ungebrauchtes Buch in makellosem Zustand ohne fehlende oder beschädigte ...
Book Title
Deep Learning
Genre
Modern & Contemporary
Original Language
English
Intended Audience
Young Adults
ISBN
9780262035613

Über dieses Produkt

Product Identifiers

Publisher
MIT Press
ISBN-10
0262035618
ISBN-13
9780262035613
eBay Product ID (ePID)
228981524

Product Key Features

Number of Pages
800 Pages
Publication Name
Deep Learning
Language
English
Subject
Intelligence (Ai) & Semantics, Computer Science
Publication Year
2016
Type
Textbook
Author
Yoshua Bengio, Ian Goodfellow, Aaron Courville
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
Dewey Edition
23
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 --
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

Artikelbeschreibung des Verkäufers

Info zu diesem Verkäufer

dunkin_bookstore

99,4% positive Bewertungen192 Tsd. Artikel verkauft

Mitglied seit Jun 2014
Antwortet meist innerhalb 24 Stunden
Angemeldet als gewerblicher Verkäufer
📚 Dunkin Bookstore - Your Ultimate Book Destination! 📖🌟 Welcome to Dunkin Bookstore! 🌟Where every page turns into a new adventure!🔹 A Treasure Trove of BooksLooking for bestsellers, classics, or ...
Mehr anzeigen
Shop besuchenKontakt

Detaillierte Verkäuferbewertungen

Durchschnitt in den letzten 12 Monaten
Genaue Beschreibung
4.9
Angemessene Versandkosten
5.0
Lieferzeit
5.0
Kommunikation
4.9

Verkäuferbewertungen (39'710)

Alle Bewertungen
Positiv
Neutral
Negativ