Zurück zur Startseite
|Eingestellt in Kategorie:

Bild 1 von 2

Deep Learning (Adaptive Computation a..., Bach, Francis - Bild 1 von 2
Deep Learning (Adaptive Computation a..., Bach, Francis - Bild 2 von 2
Ähnlichen Artikel verkaufen?
Selbst verkaufen

Deep Learning (Adaptive Computation a..., Bach, Francis

worldofbooksinc
(231761)
Angemeldet als gewerblicher Verkäufer
Mehr Artikel des Verkäufers
Verkäufer kontaktieren
US $40,99
Ca.CHF 32,43
Artikelzustand:
Sehr gut
Mehr als 10 verfügbar
Ganz entspannt. Kostenloser Versand & Rückversand.
Versand:
Kostenlos USPS Media MailTM.
Standort: Montgomery Illinois, USA
Lieferung:
Lieferung zwischen Sa, 5. Jul und Mi, 9. Jul nach 94104 bei heutigem Zahlungseingang
Wir wenden ein spezielles Verfahren zur Einschätzung des Liefertermins an – in diese Schätzung fließen Faktoren wie die Entfernung des Käufers zum Artikelstandort, der gewählte Versandservice, die bisher versandten Artikel des Verkäufers und weitere ein. Insbesondere während saisonaler Spitzenzeiten können die Lieferzeiten abweichen.
Rücknahme:
30 Tage Rückgabe. Verkäufer zahlt Rückversand.
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.:314739226183
Zuletzt aktualisiert am 01. Jul. 2025 19:58:00 MESZAlle Änderungen ansehenAlle Änderungen ansehen

Artikelmerkmale

Artikelzustand
Sehr gut: Buch, das nicht neu aussieht und gelesen wurde, sich aber in einem hervorragenden Zustand ...
Book Title
Deep Learning (Adaptive Computation and Machine Learning Series)
ISBN
0262035618
EAN
9780262035613
Release Title
Deep Learning (Adaptive Computation and Machine Learning Series)
Artist
Bach, Francis
Brand
N/A
Colour
N/A

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

worldofbooksinc

97,7% positive Bewertungen•1.1 Mio. Artikel verkauft

Mitglied seit Feb 2020
Antwortet meist innerhalb 24 Stunden
Angemeldet als gewerblicher Verkäufer
In 2002, World of Books Group was founded on an ethos to do good, protect the planet and support charities by enabling more goods to be reused. Since then, we've grown into to a global company ...
Mehr anzeigen
Shop besuchenKontakt

Detaillierte Verkäuferbewertungen

Durchschnitt in den letzten 12 Monaten
Genaue Beschreibung
4.8
Angemessene Versandkosten
5.0
Lieferzeit
5.0
Kommunikation
5.0

Verkäuferbewertungen (267'375)

Alle Bewertungen
Positiv
Neutral
Negativ
Alle Bewertungen ansehen

Noch mehr entdecken: