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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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Recognizing music genres with the Raspberry Pi Pico

Here we are, ready to finalize our application on the Raspberry Pi Pico.

In this final recipe, we will deploy the TensorFlow Lite model to recognize the music genre from audio clips recorded with the microphone connected to the microcontroller.

Getting ready

The application we will design in this recipe aims to continuously record a 1-second audio clip and run the model inference, as illustrated in the following image:

Figure 6.17: Recording and processing tasks running sequentially

From the task execution timeline shown in the preceding image, you can observe that the feature extraction and model inference are always performed after the audio recording and not concurrently. Therefore, it is evident that we do not process some segments of the live audio stream.

Unlike a real-time keyword spotting (KWS) application, which should capture and process all pieces of the audio stream to never miss any spoken...

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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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