Deep learning : a practitioner's approach

How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, par...

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Bibliographic Details
Main Authors: Patterson, Josh, (Author), Gibson, Adam, (Author)
Format: eBook
Language: English
Published: Sebastopol, CA : O'Reilly Media, Inc., 2017.
Edition: First edition.
Subjects:
ISBN: 9781491914236
9781491914212
9781491914250
Physical Description: 1 online zdroj (507 stran) : barevné ilustrace

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100 1 |a Patterson, Josh,  |e author. 
245 1 0 |a Deep learning :  |b a practitioner's approach /  |c Josh Patterson and Adam Gibson. 
250 |a First edition. 
264 1 |a Sebastopol, CA :  |b O'Reilly Media, Inc.,  |c 2017. 
264 4 |c ©2017 
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500 |a Includes index. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty univerzity 
520 |a How can machine learning--especially deep neural networks--make a real difference in your organization? This hands-on guide not only provides practical information, but helps you get started building efficient deep learning networks. The authors provide the fundamentals of deep learning--tuning, parallelization, vectorization, and building pipelines--that are valid for any library before introducing the open source Deeplearning4j (DL4J) library for developing production-class workflows. Through real-world examples, you'll learn methods and strategies for training deep network architectures and running deep learning workflows on Spark and Hadoop with DL4J.- Resumé vydavatel 
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700 1 |a Gibson, Adam,  |e author. 
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