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Deep Learning

A Practitioner's Approach

by Josh Patterson Author · Adam Gibson Author

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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
  • Publication Details

    Publisher:
    O'Reilly Media
    Publication Date:
    2017

    Format

    • Kindle Book
    • OverDrive Read 17.3 MB
    • Adobe PDF eBook 19.4 MB
    • Adobe EPUB eBook 17.2 MB
    • Open PDF eBook 19.5 MB
    • Open EPUB eBook 17.2 MB

    Josh Patterson (Author)

    Josh Patterson currently runs a consultancy in the big data machine learning / deep learning space. Previously Josh worked as a Principal Solutions Architect at Cloudera and as a machine learning / distributed systems engineer at the Tennessee Val...

    More about Josh Patterson

    Adam Gibson (Author)

    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 han...

    More about Adam Gibson
    Deep Learning
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