Published by O'Reilly Media, Incorporated, 2017
ISBN 10: 1491914254 ISBN 13: 9781491914250
Language: English
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Published by O'Reilly Media, Incorporated, 2017
ISBN 10: 1491914254 ISBN 13: 9781491914250
Language: English
Seller: Better World Books: West, Reno, NV, U.S.A.
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Published by O'Reilly Media 2016-03-31, 2016
ISBN 10: 1491914254 ISBN 13: 9781491914250
Language: English
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Add to basketPaperback. Condition: New. Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning-especially deep neural networks-make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their 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. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J's workflow tool Learn how to use DL4J natively on Spark and Hadoop.
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Add to basketCondition: Good. [ No Hassle 30 Day Returns ][ Ships Daily ] [ Underlining/Highlighting: NONE ] [ Writing: NONE ] [ Edition: first ] Publisher: O'Reilly Media Pub Date: 11/25/2015 Binding: Paperback Pages: 200 first edition.
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Paperback. Condition: New. Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning-especially deep neural networks-make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their 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. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J's workflow tool Learn how to use DL4J natively on Spark and Hadoop.
Published by Oreilly & Associates Inc, 2017
ISBN 10: 1491914254 ISBN 13: 9781491914250
Language: English
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Add to basketCondition: New. How can machine learning-especially deep neural networks-make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learn.
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Paperback. Condition: New. Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning-especially deep neural networks-make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their 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. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J's workflow tool Learn how to use DL4J natively on Spark and Hadoop.
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Add to basketPaperback. Condition: New. Although interest in machine learning has reached a high point, lofty expectations often scuttle projects before they get very far. How can machine learning-especially deep neural networks-make a real difference in your organization? This hands-on guide not only provides the most practical information available on the subject, but also helps you get started building efficient deep learning networks. Authors Adam Gibson and Josh Patterson provide theory on deep learning before introducing their 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. Dive into machine learning concepts in general, as well as deep learning in particular Understand how deep networks evolved from neural network fundamentals Explore the major deep network architectures, including Convolutional and Recurrent Learn how to map specific deep networks to the right problem Walk through the fundamentals of tuning general neural networks and specific deep network architectures Use vectorization techniques for different data types with DataVec, DL4J's workflow tool Learn how to use DL4J natively on Spark and Hadoop.
Published by Oreilly & Associates Inc, 2017
ISBN 10: 1491914254 ISBN 13: 9781491914250
Language: English
Seller: Revaluation Books, Exeter, United Kingdom
Paperback. Condition: Brand New. 507 pages. 10.00x7.25x1.25 inches. In Stock. This item is printed on demand.