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You're reading from  TinyML Cookbook - Second Edition

Product typeBook
Published inNov 2023
PublisherPackt
ISBN-139781837637362
Edition2nd Edition
Concepts
Machine Learning
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Author (1)
Gian Marco Iodice
Gian Marco Iodice
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Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice

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Live classifications with a smartphone

When discussing model testing, we usually refer to evaluating the trained model on the test dataset. However, model testing in Edge Impulse is more than that.

In this recipe, we will learn how to test model performance on the test dataset and show a way to perform live classifications with a smartphone.

Getting ready

In Edge Impulse, there are two ways to evaluate the accuracy of a model:

  • Model testing on the test dataset: We assess the accuracy using the test dataset. The test dataset provides an unbiased evaluation of model effectiveness because the samples are not used directly or indirectly during training.
  • Live classification: This is a unique feature of Edge Impulse whereby we can record new samples from a smartphone or a supported device (for example, the Arduino Nano).

The live classification approach benefits from testing the trained model in the real world before deploying...

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TinyML Cookbook - Second Edition
Published in: Nov 2023Publisher: PacktISBN-13: 9781837637362
© 2023 Packt Publishing Limited All Rights Reserved

Author (1)

author image
Gian Marco Iodice

Gian Marco Iodice is team and tech lead in the Machine Learning Group at Arm, who co-created the Arm Compute Library in 2017. The Arm Compute Library is currently the most performant library for ML on Arm, and it's deployed on billions of devices worldwide – from servers to smartphones. Gian Marco holds an MSc degree, with honors, in electronic engineering from the University of Pisa (Italy) and has several years of experience developing ML and computer vision algorithms on edge devices. Now, he's leading the ML performance optimization on Arm Mali GPUs. In 2020, Gian Marco cofounded the TinyML UK meetup group to encourage knowledge-sharing, educate, and inspire the next generation of ML developers on tiny and power-efficient devices.
Read more about Gian Marco Iodice

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