Deep Learning
A Practitioner's Approach
Publisher: O'Reilly Media
Final Release Date: August 2016
Pages: 400

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Looking for one central source where you can learn key findings on machine learning? Deep Learning: A Practitioner's Approach provides developers and data scientists with the most practical information available on the subject, including deep learning theory, best practices, and use cases.

Authors Adam Gibson and Josh Patterson present the latest relevant papers and techniques in a non­academic manner, and implement the core mathematics in their DL4J library. If you work in the embedded, desktop, and big data/Hadoop spaces and really want to understand deep learning, this is your book.

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oreillyDeep Learning

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Useful book

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  • Easy to understand
  • Helpful examples


  • Too basic

Best Uses

  • Intermediate
  • Novice

Comments about oreilly Deep Learning:

The initial material is fairly basic and don't expect it to go into any theoretical depth. However, as a fast and not too dirty intro to deep learning it's very nice. The examples and material are based on DL4J, and are a good start.

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March 2017 (est.)