Design Guide: How ML Can Be Implemented Using Less Complex & Lower Power MCUs
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Design Guide: How ML Can Be Implemented Using Less Complex & Lower Power MCUs

Machine learning is now being applied in many areas of everyday life. Unlike financial and scientific applications, which require significant computing power for machine learning to deliver results, the internet of things (IoT) and edge-based applications have limited computing and connectivity resources available for this purpose. In this article, we explore how machine learning can be implemented using less complex and lower power microcontrollers, an approach commonly referred to as TinyML.
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