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

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.

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  • Embedded Systems Engineers
  • Data Scientists
  • Software Developers
  • Electronics Hobbyists
  • AI Research Scientists

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Featured Content
  • 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
  • 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    • Outdated Information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  • Out of date!

    The book is out of date, some conceptions just skipped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    • Outdated Information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
  • See All Reviews
Sentiment Analysis
17 Net Promoter
Score
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