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
 
3.7

(based on 3 reviews)

Ratings Distribution

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    (1)

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    (1)

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67%

of respondents would recommend this to a friend.

Pros

  • Helpful examples (3)

Cons

No Cons

Best Uses

No Best Uses

Reviewed by 3 customers

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(2 of 3 customers found this review helpful)

 
2.0

Not great but not terrible either

By Abel

from Washington, DC

About Me Developer, Maker

Verified Buyer

Pros

  • Helpful examples

Cons

  • Too basic

Best Uses

  • Novice

Comments about oreilly Deep Learning:

two hundred pages of filler before getting to actual DL.

(0 of 1 customers found this review helpful)

 
5.0

"I would buy this product again and again"

By thierry

from FRANCE

About Me Designer

Verified Buyer

Pros

  • Accurate
  • Concise
  • Easy to understand
  • Helpful examples
  • Well-written

Cons

    Best Uses

    • Expert
    • Intermediate

    Comments about oreilly Deep Learning:

    Hi There !!
    Very Brilliant Book which depicted several uncovered under the hood tricks among all published books which i have ever seen and this book should serve as one my Key reference point in Deep Learning well written and described in a such conciseness ramming flow principles conjugated manner well fetched with own personal taste actually and this Marvelous Book would extend and enrich all my full entire collection, so many special thanks and my full gratitude to the Authors for sharing his expertises and broad knowledges visions within Data-scientists Community
    Thierry
    Best Regards
    PS:GOD BLESS AMERICA

    (2 of 2 customers found this review helpful)

     
    4.0

    Useful book

    By Why do I need a nickname?

    from Why do you need my location?

    About Me Developer

    Verified Buyer

    Pros

    • Easy to understand
    • Helpful examples

    Cons

    • 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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