Fundamentals of Deep Learning
Designing Next-Generation Machine Intelligence Algorithms
Publisher: O'Reilly Media
Final Release Date: June 2015
Pages: 250

With Early Release ebooks, you get books in their earliest form—the author's raw and unedited content as he or she writes—so you can take advantage of these technologies long before the official release of these titles. You'll also receive updates when significant changes are made, new chapters as they're written, and the final ebook bundle.

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research that is paving the way for modern machine learning. This book uses exposition and examples to help you understand major concepts in this complicated field.

Large companies such as Google, Microsoft, and Facebook have taken notice, and are actively growing in-house deep learning teams. For the rest of us however, deep learning is still a pretty complex and difficult subject to grasp. If you have a basic understanding of what machine learning is, have familiarity with the Python programming language, and have some mathematical background with calculus, this book will help you get started.

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oreillyFundamentals of Deep Learning
 
3.6

(based on 17 reviews)

Ratings Distribution

  • 5 Stars

     

    (9)

  • 4 Stars

     

    (3)

  • 3 Stars

     

    (0)

  • 2 Stars

     

    (0)

  • 1 Stars

     

    (5)

71%

of respondents would recommend this to a friend.

Pros

  • Easy to understand (10)
  • Helpful examples (10)
  • Well-written (10)
  • Accurate (8)
  • Concise (6)

Cons

No Cons

Best Uses

  • Intermediate (10)
  • Novice (7)
  • Student (4)
    • Reviewer Profile:
    • Developer (10), Educator (5)

Reviewed by 17 customers

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4.0

So far, so good!

By Speaker to Computers

from Washington DC

About Me Developer, Sys Admin

Verified Buyer

Pros

  • Accurate
  • Helpful examples
  • Well-written

Cons

    Best Uses

    • Intermediate

    Comments about oreilly Fundamentals of Deep Learning:

    Based on the content available so far (Chs. 1-6), this is an excellent introduction to deep neural network techniques, and in particular clarifies why deep networks are operationally different from their simpler precursors like perceptrons. The recently-updated Chapter 6 includes a long-awaited, cogent and complete description of the deep-network auto-encoder strategy, which is how deep neural networks are used to do feature extraction.

    I have one minor complaint, which is that many of the examples are very strongly tool-centered. This is high value for reproducing the results in TensorFlow (the tool used in this book), which is open-source and widely available, but I feel that the examples would be enhanced if they were also accompanied by a more detailed tool-agnostic description of the steps. The danger is that this might bog down the narrative, of course, so perhaps I should be careful what I wish for, but that's what has struck me so far.

    (3 of 3 customers found this review helpful)

     
    1.0

    This book is a scam

    By Frank

    from Dublin

    About Me Developer

    Verified Reviewer

    Comments about oreilly Fundamentals of Deep Learning:

    As a number of other reviewers have noted, this book is not even 50% complete. O'Reilly, what are you going to do about this? You can't just offer books for pre-release purchase and then not finish the book - and this is after a full year of waiting. What's going on?

    Will you be offering a refund?

    Regards,
    A usually happy O'Reilly customer, who will be looking elsewhere in future for his tech book needs, if this is not dealt with.

    (5 of 5 customers found this review helpful)

     
    1.0

    Full Price; Half Book

    By Richard

    from Tampa, FL

    Verified Reviewer

    Pros

    • Easy to understand

    Cons

      Best Uses

        Comments about oreilly Fundamentals of Deep Learning:

        I purchased this book with the impression that it would be completed soon since it is on a rapidly evolving topic which has a limited lifetime.

        14 months later and the book is not even 50% complete and the web page that a link to see the release history has no information about upcoming releases.

        I believe that Oreilly should refund my money and quit offering it for sale even with the disclaimer that it is an early release version. 14 months for a current technical topic is a lifetime.

        (1 of 4 customers found this review helpful)

         
        5.0

        Great book

        By mcasl

        from León, Spain

        About Me Educator, Researcher

        Verified Reviewer

        Pros

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

        Cons

        • Not comprehensive enough

        Best Uses

        • Intermediate
        • Novice

        Comments about oreilly Fundamentals of Deep Learning:

        I am reading the early released version of the book. So far the book provides very clear explanations and I am looking forward to read more chapters as they are ready.

        (4 of 4 customers found this review helpful)

         
        4.0

        Pretty good so far

        By Robert

        from San Jose, CA

        Verified Buyer

        Comments about oreilly Fundamentals of Deep Learning:

        It's pretty good so far, but it clearly needs some proofreading and it really needs to be finished. Is there a schedule?

        (2 of 2 customers found this review helpful)

         
        5.0

        Love the new chapters

        By Abhijit

        from Cambridge, MA

        About Me Developer

        Pros

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

        Cons

          Best Uses

          • Intermediate

          Comments about oreilly Fundamentals of Deep Learning:

          The new table of contents more appropriately reflects the new progress in the field. I'm glad to see that the author is not getting left behind by the field. The two new chapters on optimization and neural networks are also spectacular. This is the first solid exposition on batch normalization that I've seen.

          (2 of 4 customers found this review helpful)

           
          5.0

          Great Explanation and a few suggestions

          By Xiao He

          from Cambridge, MA

          About Me Developer, Graduate Student

          Verified Reviewer

          Pros

          • Easy to understand
          • Helpful examples
          • Well-written

          Cons

            Best Uses

            • Intermediate

            Comments about oreilly Fundamentals of Deep Learning:

            Nikhil does great job teaching concepts of deep learning. I know it is early release, but there is new work not reflected in the table of concepts. I would like to see some additional chapter covering new work in neural turing machine and how neural network are used to solve Go.

            (6 of 13 customers found this review helpful)

             
            1.0

            Still only 3 chapters avaliable

            By Maik

            from The Netherlands

            About Me Educator

            Comments about oreilly Fundamentals of Deep Learning:

            Last updated July 2015, with chapter 3 to be the last one released.
            Never judge a book by its cover... but after waiting more than 6 months for a new chapter, I think 4 or even 5 stars are a bit overrated.

            (3 of 4 customers found this review helpful)

             
            5.0

            Superb introduction

            By raistlin de Majere

            from Vienna, Austria

            About Me Developer

            Verified Buyer

            Pros

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

            Cons

              Best Uses

              • Intermediate
              • Novice
              • Student

              Comments about oreilly Fundamentals of Deep Learning:

              Following neural networks - since the late 90s as a personal/private interest - this book really gives a great introduction AND explanation intro every aspect.
              While of course everything can be found on the Internet, here you get everything in one place and without expecting anything from the reader.
              I hope further chapters get released soon.
              And maybe deeplearning4j gets at least mentioned in an Appendix to show alternatives to the pragmatic practitioner ;-)

              (3 of 7 customers found this review helpful)

               
              5.0

              Looking forward to the rest of the book!

              By William

              from Cambridge, MA

              About Me Developer

              Pros

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

              Cons

                Best Uses

                • Intermediate
                • Novice
                • Student

                Comments about oreilly Fundamentals of Deep Learning:

                So far this has been a great read. The author brings a lot of clarity to some complex concepts. I hope the book will be finished soon!

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