Machine Learning with the Raspberry Pi

Experiments with Data and Computer Vision

Authors: Norris, Donald J.

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  • Build on the concepts provided in "Beginning Artificial Intelligence with the Raspberry Pi"
  • Integrate AI and ML concepts and algorithms into both hobbyist and commercial projects
  • Work with real machine learning experiments and modify them to fit your own needs and interests
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eBook $24.99
price for USA (gross)
  • ISBN 978-1-4842-5174-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $34.99
price for USA
  • ISBN 978-1-4842-5173-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.
About this book

Using the Pi Camera and a Raspberry Pi board, expand and replicate interesting machine learning (ML) experiments.  This book provides a solid overview of ML and a myriad of underlying topics to further explore. Non-technical discussions temper complex technical explanations to make the hottest and most complex topic in the hobbyist world of computing understandable and approachable.

Machine learning, also commonly referred to as deep learning (DL), is currently being integrated into a multitude of commercial products as well as widely being used in industrial, medical, and military applications.  It is hard to find any modern human activity, which has not been "touched" by artificial intelligence (AI) applications. Building on the concepts first presented in Beginning Artificial Intelligence with the Raspberry Pi, you’ll go beyond simply understanding the concepts of AI into working with real machine learning experiments and applying practical deep learning concepts to experiments with the Pi board and computer vision. 

What you learn with Machine Learning with the Raspberry Pi can then be moved on to other platforms to go even further in the world of AI and ML to better your hobbyist or commercial projects.

What You'll Learn

  • Acquire a working knowledge of current ML 
  • Use the Raspberry Pi to implement ML techniques and algorithms
  • Apply AI and ML tools and techniques to your own work projects and studies

Who This Book Is For

Engineers and scientists but also experienced makers and hobbyists.  Motivated high school students who desire to learn about ML can benefit from this material with determination.

About the authors

Donald Norris is an avid electronics hobbyist and maker. He is also an electronics engineer with an advanced degree in Production Management. Don is retired from civilian government service with the US Navy, where he specialized in acoustics and digital signal processing. He also has more than a dozen years’ experience as a professional software developer using C, C#, C++, Python, and Java, as well as five years’ experience as a certified IT security consultant.

Table of contents (9 chapters)

Table of contents (9 chapters)
  • Introduction to machine learning (ML) with the Raspberry Pi (RasPi)

    Pages 1-47

    Norris, Donald J.

  • Exploration of ML data models: Part 1

    Pages 49-133

    Norris, Donald J.

  • Exploration of ML data models: Part 2

    Pages 135-212

    Norris, Donald J.

  • Preparation for deep learning

    Pages 213-277

    Norris, Donald J.

  • Practical deep learning ANN demonstrations

    Pages 279-334

    Norris, Donald J.

Buy this book

eBook $24.99
price for USA (gross)
  • ISBN 978-1-4842-5174-4
  • Digitally watermarked, DRM-free
  • Included format: PDF, EPUB
  • ebooks can be used on all reading devices
  • Immediate eBook download after purchase
Softcover $34.99
price for USA
  • ISBN 978-1-4842-5173-7
  • Free shipping for individuals worldwide
  • Usually dispatched within 3 to 5 business days.

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Bibliographic Information

Bibliographic Information
Book Title
Machine Learning with the Raspberry Pi
Book Subtitle
Experiments with Data and Computer Vision
Authors
Copyright
2020
Publisher
Apress
Copyright Holder
Donald J. Norris
eBook ISBN
978-1-4842-5174-4
DOI
10.1007/978-1-4842-5174-4
Softcover ISBN
978-1-4842-5173-7
Edition Number
1
Number of Pages
IX, 568
Number of Illustrations
229 b/w illustrations
Topics