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Deep Learning: A Practitioner's Approach by [Patterson, Josh, Gibson, Adam]
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Deep Learning: A Practitioner's Approach 1st Edition, Kindle Edition

4.0 out of 5 stars 1 customer review
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Length: 538 pages Enhanced Typesetting: Enabled Page Flip: Enabled
Language: English

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Product description

Product Description

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

About the Author

Josh Patterson is CEO of Patterson Consulting, a solution integrator at the intersection of big data and applied machine learning. In this role, he brings his unique perspective blending a decade of big data experience and wide-ranging deep learning experience to Fortune 500 projects. At the Tennessee Valley Authority (TVA), Josh drove the integration of Apache Hadoop for large-scale data storage and processing of smart grid phasor measurement unit (PMU) data. Post-TVA, Josh was a principal solutions architect for a young Hadoop startup named Cloudera (CLDR), as employee 34. After leaving Cloudera, Josh co-founded the Deeplearning4j project and co-wrote Deep Learning: A Practitioner's Approach (O'Reilly Media). Josh was also the VP of Field Engineering for Skymind.

Adam Gibson is a deep­-learning specialist based in San Francisco who works with Fortune 500 companies, hedge funds, PR firms and startup accelerators to create their machine-­learning projects. Adam has a strong track record helping companies handle and interpret big real­time data. Adam has been a computer nerd since he was 13, and actively contributes to the open­-source community through deeplearning4j.org.


Product details

  • Format: Kindle Edition
  • File Size: 21950 KB
  • Print Length: 538 pages
  • Simultaneous Device Usage: Unlimited
  • Publisher: O'Reilly Media; 1 edition (28 July 2017)
  • Sold by: Amazon Australia Services, Inc.
  • Language: English
  • ASIN: B074D5YF1D
  • Text-to-Speech: Enabled
  • X-Ray:
  • Word Wise: Not Enabled
  • Enhanced Typesetting: Enabled
  • Average Customer Review: 4.0 out of 5 stars 1 customer review
  • Amazon Bestsellers Rank: #336,201 Paid in Kindle Store (See Top 100 Paid in Kindle Store)

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Amazon.com: 4.3 out of 5 stars 21 reviews
Mike Dillinger
3.0 out of 5 starsA practical guide, not a good intro to key concepts
19 March 2018 - Published on Amazon.com
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12 people found this helpful
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3.0 out of 5 starsA deep learning book in JAVA only
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Stergios Papadimitriou
5.0 out of 5 starsAn excellent practical book for applying deep learning on real projects
27 August 2018 - Published on Amazon.com
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4 people found this helpful
James C. Westland
3.0 out of 5 starsMore a less a rehash of material that is online.
21 April 2018 - Published on Amazon.com
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5 people found this helpful