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02933cam a2200529Ki 4500
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20210114162157
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cr cnu---unuuu
190831s2019 enk ob 000 0 eng d
▼a GBB9E0688
▼2 bnb
▼a 019505044
▼2 Uk
▼a 9781789347883
▼q (electronic bk.)
▼a 1789347882
▼q (electronic bk.)
▼z 9781789340990
▼q (pbk.)
▼a 2228072
▼b (N$T)
▼a (OCoLC)1112426164
▼a E9677C19-5AAC-4D14-A929-D72AB4297B2A
▼b OverDrive, Inc.
▼n http://www.overdrive.com
▼a EBLCP
▼b eng
▼e rda
▼e pn
▼c EBLCP
▼d TEFOD
▼d EBLCP
▼d TEFOD
▼d UKMGB
▼d OCLCF
▼d UKAHL
▼d OCLCQ
▼d N$T
▼d 248023
▼a Q325.5
▼a 006.3/1
▼2 23
▼a Seneque, Gareth,
▼e author.
▼a Hands-on deep learning with Go:
▼b a practical guide to building and implementing neural network models using Go /:
▼c Gareth Seneque, Darrell Chua.
▼a Birmingham, UK:
▼b Packt Publishing,
▼c [2019].
▼a 1 online resource (228 pages).
▼a text
▼b txt
▼2 rdacontent
▼a computer
▼b n
▼2 rdamedia
▼a online resource
▼b nc
▼2 rdacarrier
▼a Includes bibliographical references.
▼a Table of ContentsIntroduction to Deep Learning in GoWhat Is a Neural Network and How Do I Train One?Beyond Basic Neural Networks -- Autoencoders and RBMsCUDA -- GPU-Accelerated TrainingNext Word Prediction with Recurrent Neural NetworksObject Recognition with Convolutional Neural NetworksMaze Solving with Deep Q-NetworksGenerative Models with Variational AutoencodersBuilding a Deep Learning PipelineScaling Deployment.
▼a The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using ...
▼a Print version record.
▼a Added to collection customer.56279.3
▼a Machine learning.
▼a Go (Computer program language)
▼a Go (Computer program language)
▼2 fast
▼0 (OCoLC)fst01893916
▼a Machine learning.
▼2 fast
▼0 (OCoLC)fst01004795
▼a Electronic books.
▼a Chua, Darrell,
▼e author.
▼i Print version:
▼a Seneque, Gareth.
▼t Hands-On Deep Learning with Go : A Practical Guide to Building and Implementing Neural Network Models Using Go.
▼d Birmingham : Packt Publishing, Limited, ©2019,
▼z 9781789340990
▼3 EBSCOhost
▼u http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=2228072
▼a Askews and Holts Library Services
▼b ASKH
▼n AH36568418
▼a ProQuest Ebook Central
▼b EBLB
▼n EBL5849398
▼a EBSCOhost
▼b EBSC
▼n 2228072
▼a 강리원
▼a eBook
▼a 92
▼b N$T
| 자료유형 : | eBook |
|---|---|
| ISBN : | 9781789347883 |
| ISBN : | 1789347882 |
| ISBN : | |
| 개인저자 : | Seneque, Gareth, author. |
| 서명/저자사항 : | Hands-on deep learning with Go: a practical guide to building and implementing neural network models using Go /: Gareth Seneque, Darrell Chua. |
| 발행사항 : | Birmingham, UK: Packt Publishing, [2019]. |
| 형태사항 : | 1 online resource (228 pages). |
| 서지주기 : | Includes bibliographical references. |
| 내용주기 : | Table of ContentsIntroduction to Deep Learning in GoWhat Is a Neural Network and How Do I Train One?Beyond Basic Neural Networks -- Autoencoders and RBMsCUDA -- GPU-Accelerated TrainingNext Word Prediction with Recurrent Neural NetworksObject Recognition with Convolutional Neural NetworksMaze Solving with Deep Q-NetworksGenerative Models with Variational AutoencodersBuilding a Deep Learning PipelineScaling Deployment. |
| 요약 : | The Go ecosystem comprises some really powerful Deep Learning tools. This book shows you how to use these tools to train and deploy scalable Deep Learning models. You will explore a number of modern Neural Network architectures such as CNNs, RNNs, and more. By the end, you will be able to train your own Deep Learning models from scratch, using ... |
| 일반주제명 : | Machine learning. -- |
| 일반주제명 : | Go (Computer program language) -- |
| 일반주제명 : | Go (Computer program language) -- |
| 일반주제명 : | Machine learning. -- |
| 개인저자 : | Chua, Darrell, author. |
| 기타형태 저록 : | Print version: Seneque, Gareth. Hands-On Deep Learning with Go : A Practical Guide to Building and Implementing Neural Network Models Using Go. Birmingham : Packt Publishing, Limited, ©2019, 9781789340990 |
| 언어 | 영어 |
| URL : |
|---|
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