Review of David Foster's Generative Deep Learning Book
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Review of David Foster's Generative Deep Learning Book

A comprehensive review of David Foster's Generative Deep Learning book, covering its strengths, weaknesses, and practicality for readers with different levels of ML knowledge.

Best for
  • Data Scientists
  • Machine Learning Engineers
  • AI Researchers
  • Software Developers
  • Educational Technologists

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Custom Date - Apr 12, 2024
Featured Content
  • very well written

    I read the first part of the book and very impressed by its explanation. However, keep in mind that the reader should be familiar with the basics of neural network

    • Positive
    • Basics of Neural Network
    Apr 19, 2021
  • Great book

    This book provides a great motivation behind studying generative models. I have found the explanations to be clear and helpful even on topics I am already familiar with.

    • Positive
    • Explanation and Clarity
    Oct 03, 2019
  • This book is the only reason I was able to get my dream job as a Machine Learning Engineer

    David Foster's Generative Deep Learning book was the only reason I was able to get my dream job as a Machine Learning Engineer (even though I have no college education...I cannot express my gratitude 🙏)

    • Positive
    • Practical Exercises
    Sep 25, 2019
  • Really good overview of topics for GAN development

    This book is a really fun read with great examples in what;s going on with not only GANs, but also their relation to their variational autoencoder cousins. The examples are fantastic and the book is written incredibly well.

    • Positive
    • Code Examples
    Sep 18, 2019
  • Pretty bad printing quality.

    Paper is super thin and images seem to have printed by a cheap printer in economy mode.

    I'm not usually picky about these things but it is very noticeable.

    Content wise is OK, I especially liked the explanation about mode collapse in GANs and justification of WGAN losses and why they work. There are many analogies to explain concepts (VAEs, GANs, etc) and but I find some of them could be better.

    • Positive
    • Quality of Book
    Aug 03, 2019
  • Great contents with lucid examples

    I am half way through the book, and I would give 5 stars to this book. I like the examples that David used to describe VAE and GAN. David is a great writer who balances technical depth and lucid examples to illustrate the key concepts. I would strongly encourage David to write technical books in the near future.

    • Positive
    • Explanation and Clarity
    Jul 24, 2019
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Sentiment Analysis
73 Net Promoter
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