Fundamentals of Deep Learning
Designing Next-Generation Machine Intelligence Algorithms
Publisher: O'Reilly Media
Final Release Date: June 2015
Pages: 300

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
 
3.8

(based on 15 reviews)

Ratings Distribution

  • 5 Stars

     

    (9)

  • 4 Stars

     

    (2)

  • 3 Stars

     

    (0)

  • 2 Stars

     

    (0)

  • 1 Stars

     

    (4)

73%

of respondents would recommend this to a friend.

Pros

  • Easy to understand (10)
  • Helpful examples (9)
  • Well-written (9)
  • Accurate (7)
  • Concise (6)

Cons

No Cons

Best Uses

  • Intermediate (9)
  • Novice (7)
  • Student (4)
    • Reviewer Profile:
    • Developer (8), Educator (5)

Reviewed by 15 customers

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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.

      (0 of 1 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.

      (3 of 3 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!

              (3 of 6 customers found this review helpful)

               
              1.0

              Compendium of already available resources

              By Raj

              from San Jose, CA

              About Me Educator

              Pros

                Cons

                • Unoriginal

                Best Uses

                • Novice

                Comments about oreilly Fundamentals of Deep Learning:

                So far this more or less seems like a compilation of resources that you can already easily find online. I'm not quite sure if it's worth the money to buy a compendium.

                (3 of 6 customers found this review helpful)

                 
                5.0

                Best / Only resource on this hot topic

                By simondlevy

                from Lexington, Virginia

                About Me Educator

                Pros

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

                Cons

                  Best Uses

                  • Novice
                  • Student

                  Comments about oreilly Fundamentals of Deep Learning:

                  I've been working in neural nets since the PDP revolution of the late 1980s, and (based on the early-release chapters I've been able to get so far), this book is shaping up to be not only the best book on deep learning, but the best overall introduction to perceptrons and hidden-layer networks. Having given up on the Theano tutorials, I was delighted to read Buduma's straightforward introduction to this core technology. If the rest of the book is anything like this early-release version, it's destined to become the must-have introduction to this burgeoning field. I plan to use it as the textbook in my AI courses from now on.

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