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Débute 4 June 2026 07:18

Se termine 4 June 2026

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Harvard University

Applications of TinyML

Découvrez le monde du Tiny Machine Learning (TinyML) et explorez ses vastes applications avec le cours "Applications du TinyML" proposé par l'Université Harvard via edX. Ce cours, faisant suite aux Fondements du Tiny ML, se penche sur la façon dont des dispositifs comme Google Home traitent des commandes telles que “OK Google” et si ces dispositifs.
Harvard University via edX

Harvard University

24 Cours


L'Université Harvard est une université de recherche privée de l'Ivy League, mondialement reconnue, située à Cambridge, dans le Massachusetts. Fondée en 1636, c'est l'une des plus anciennes institutions d'enseignement supérieur aux États-Unis.

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Discover the world of Tiny Machine Learning (TinyML) and explore its vast applications with the "Applications of TinyML" course provided by Harvard University through edX. This course, following the Foundations of Tiny ML, delves into how devices like Google Home process commands like “OK Google,” and whether these devices are constantly listening.

Through engaging real-world case studies led by industry experts, you'll confront deployment challenges in tiny or deeply embedded devices.

Embark on a journey through the intricacies of using sensor data for recognizing gestures and voices, with a keen focus on the neural networks powering applications such as “OK Google,” “Alexa,” and various smartphone functionalities across Android and Apple systems. This course offers a deep dive into the programming behind these applications, covering key areas like training and inference within neural networks.

Beyond the technical aspects, you'll uncover real-world industry applications of TinyML including Keyword Spotting, Visual Wake Words, Anomaly Detection, Dataset Engineering, and the principles of Responsible Artificial Intelligence.

As a part of the TinyML Professional Certificate program, this course positions you at the forefront of one of deep learning's most dynamic and accessible fields, showcasing the code behind some of the most extensively used TinyML devices worldwide.

Categories include:

Machine Learning Courses, Anomaly Detection Courses, Deep Learning Courses, Neural Networks Courses.


Enseigné par

Vijay Janapa Reddi


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