Review of Generative Deep Learning Kindle Edition
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Review of Generative Deep Learning Kindle Edition

Exclusive Customer Feedback Analysis on Generative Deep Learning

This review is for the Kindle edition of the book Generative Deep Learning. While the content and examples are good, the electronic version has poor quality with skipped type settings and substituted symbols. The book covers key techniques in generative AI but lacks a section on evaluating the quality of generated images. Overall, it is a helpful resource for understanding generative ML, but the formatting of mathematical formulas is a drawback.

Source: Amazon Product Reviews of Generative Deep Learning eBook :

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Customer Feedback Analysis of Generative Deep Learning eBook :

Uncover insights from customer feedback on the Kindle edition of Generative Deep Learning. Essential for tech professionals.

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Custom Date - Dec 28, 2024
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  • Give a very good understanding of the field.
    Helps create quickly easy models and gives a good grasp of the math underlying the models

    Sentiment
    • Positive
    Content
    • Explanation of Concepts
    Sep 12, 2023

  • This was a great read to understand how generative AI works, at the right level of detail and very much up to date. The content structure is good to learn the theory starting from the basics and then gradually layering the most complex and recent evolutions. The accompanying TensorFlow workbooks help with practical examples that can be followed.
    One negative note: the Kindle version is low quality when it comes to mathematical formulas, impossible to read.

    Sentiment
    • Positive
    Content
    • Book Quality
    Aug 30, 2023
  • highly recommended for beginers

    This is a lovely book. It is readable and explains the principles behind algorithms clearly.

    Sentiment
    • Positive
    Content
    • Explanation of Concepts
    Aug 25, 2023
  • Code demos don't work

    The big-picture ideas are good, but without the ability to practice the code included, I can't recommend it.
    (I spent over ten hours trying to work through compatibility problems, outdated libraries, and unsupported software. In the end, I wasn't able to run a single example code example from this book. I'm not a noob either. I've managed to install and run inference / training on dozens of open source AI projects, for image gen, LLMs, music, voice synthesis, style transfer, NeRFs, and 3d model gens. This book uses Docker and Jupyter notebooks, which I've never seen any other project use ever. They're not supported on modern systems. Obsolete.)

    Sentiment
    • Negative
    Content
    • Code Examples
    Aug 16, 2023
  • Explains Generative ML Very Well

    David did a great job with this book. He very clearly explains how generative ML (deep learning, AI, etc) works from first principles. Very helpful if you're interested in GAI from a fundamental level.

    Sentiment
    • Positive
    Content
    • Explanation of Concepts
    Jul 02, 2023
  • The book I was looking for

    Amazing book, for me the best thing about it is that there are many well-sourced and working code and data examples which are explained clearly in the text.

    Sentiment
    • Positive
    Content
    • Code Examples
    Jun 09, 2023
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