{"id":45815,"date":"2021-06-14T13:34:30","date_gmt":"2021-06-14T05:34:30","guid":{"rendered":"\/blog\/?p=45815"},"modified":"2024-02-21T07:19:55","modified_gmt":"2024-02-21T07:19:55","slug":"everything-about-tinyml-basics-courses-projects-more","status":"publish","type":"post","link":"https:\/\/www.seeedstudio.com\/blog\/2021\/06\/14\/everything-about-tinyml-basics-courses-projects-more\/","title":{"rendered":"Everything About TinyML – Basics, Courses, Projects & More!"},"content":{"rendered":"\n

Updated on Feb 6th, 2024<\/strong><\/p>\n\n\n\n

TinyML is one of the hottest trends in the embedded computing field right now, with 2.5 billion TinyML-enabled devices estimated to reach the market in the next decade and a projected market value exceeding $70 billion in just five years. If you want to get in on what all the excitement is about but aren\u2019t sure where to start, this one-stop guide is specifically for you. Learn about what TinyML is, the opportunities it offers, and how anybody can get themselves started in this exciting field!<\/p>\n\n\n\n

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What is TinyML?<\/strong><\/h2>\n\n\n\n
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Tiny Machine Learning (TinyML)<\/a> is a field of machine learning that focuses on the development and deployment of ML models on low power, low-footprint microcontroller devices like an Arduino<\/a>, for example.<\/p>\n\n\n\n

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Machine learning is a field of computer systems that aims to develop self-improving algorithms and statistical models. This is done with massive amounts of data, which a model analyses and extracts patterns from in order to learn and improve on a given task. This seemingly simple paradigm has led to groundbreaking advancements in complex tasks like forecasting, anomaly detection, and computer vision!<\/p>\n\n\n\n

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The Benefits & Importance of TinyML<\/strong><\/h3>\n\n\n\n
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Why is TinyML so important, you ask? Simple – because it\u2019s tiny!<\/p>\n\n\n\n

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The microcontrollers that TinyML models are designed for are small and power efficient<\/strong>; capable of running on battery power for years at a time! Furthermore, these microcontrollers are far more affordable<\/strong> than full-sized computers or servers, which makes their use far more accessible and practical<\/strong> for small businesses or even individuals. This unique combination of power efficiency and affordability also means that TinyML is perfectly poised for large-scale applications<\/strong> in embedded computing applications, like IoT!<\/p>\n\n\n\n

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At the same time, TinyML is a subset of what is known as Edge AI, or edge artificial intelligence. It leverages the advantages of edge computing – computing in the local space as opposed to in the cloud – to deliver several key advantages, namely:<\/p>\n\n\n\n

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