TinyML: A quick guide to Understanding Machine learning at the Edge.

Author(s): Jair Ribeiro

Originally published on Towards AI.

An introduction to the open source framework in a nutshell

Source: My latest specialization training at Harvard University

Machine learning is changing the world because it lets computers learn from data, find trends, and predict what will happen.

It enables systems to become self-sufficient, precise, and dependable. Users demand high-quality mobile experiences that are speedy, responsive, and dependable. However, these experiences necessitate significant processing at the edge and in the cloud.

Furthermore, IoT endpoints must function autonomously despite having limited bandwidth, storage, and processing power. These constraints raise the necessity for machine learning models to be computed at the edge.

This week, I had the chance to refresh and deepen my understanding of TinyML… Read the full blog for free on Medium.

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Published via Towards AI