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Comprehensive Guide to TinyML: Machine Learning on Resource-Limited Devices

Comprehensive Guide to TinyML: Machine Learning on Resource-Limited Devices

30 recent reviews.

A comprehensive guide to TinyML, this book provides a practical approach to edge computing and machine learning on resource-limited devices. It covers topics like deploying models for boards, working with TensorFlow, and understanding the code it generates. However, some readers have noted that the book is not up to date with the latest TensorFlow version and the provided links do not work. Despite these issues, the book offers valuable insights for data enthusiasts looking to explore new sources of data and interact with the physical world.

TinyML: Machine Learning with TensorFlow Lite on Arduino and Ultra-Low-Power Microcontrollers:
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  • Decent book, but out-of-date. Needs to be revised.

    This is a decent introductory book, but significant portions of TensorFlow Lite have changed since the book was written. As a result, the high level concepts still apply, but the specific details described are no longer accurate.

    Sentiment
    • None
    Content
    • Outdated Information
  • Links for downloads are out of date

    Tried using the first few links to download from GitHub and none of the links work. The book is worthless without being able to download the example excercises.

    Sentiment
    • Negative
    Content
    • Resource Availability
  • Every code link in the book are broken

    Looks like every git link in the code is removed, and entire Arduino code base is deleted

    Sentiment
    • Negative
    Content
    • Code Examples
  • Did not work on my Arduino Nano - needs fixes to code.

    Mostly good and useful information probably would be better to remove the boilerplate code in the book and just point people to the relevant GitHub projects.

    Sentiment
    • None
    Content
    • Code Examples
  • This book is very thorough

    It has the right amount of details and combines theory and hands-on approach. I have totally enjoyed reading it, and looking forward to apply the gained knowledge to real applications.

    Sentiment
    • Positive
    Content
    • Hands-on Approach
  • Not worth for money. Content not good

    High cost but no good content. Some projects are given. No depth discussion. Dont buy it.

    Sentiment
    • Negative
    Content
    • Outdated Information
  • Must have for edge computing lovers!

    Its probably the only book that is available on tinyML. Quite practical and no-nonsense approach to edge computing.

    Sentiment
    • Positive
    Content
    • Hands-on Approach
  • Easy to understand

    The book is easy to understand, and the code is available on the internet for different boards, so it is easy to follow along.

    Sentiment
    • Positive
    Content
    • Resource Availability
  • Out of date!

    The book is out of date, some conceptions just skipped

    Sentiment
    • Negative
    Content
    • Outdated Information
  • Excellent intro

    Excellent introduction to machine learning on the edge. Well written and with easily accessible code examples.

    Sentiment
    • Positive
    Content
    • Machine Learning
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Sentiment Analysis

17 Net Promoter
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