Deep Learning : A Practitioner's Approach

By:

Patterson, Josh

Contributor(s):

Gibson, Adam

Material type: Text

TextPublisher: O'Reilly, 2021Description: 528 pISBN:

9789352136049

Subject(s):

DDC classification:

006.31 PAT

Summary: 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.-- Source other than Library of Congress.

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Holdings
Item type	Current library	Collection	Call number	Status	Date due	Barcode
Books	NMIT General Stacks	Artificial Intelligence and Data Science	006.31 PAT (Browse shelf(Opens below))	Available		50260

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.-- Source other than Library of Congress.

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