Vidushhi Panda

This section provides practical guidance for successfully deploying Tiny Machine Learning (TinyML) on edge devices. It covers best practices for optimizing models to run efficiently on resource-constrained hardware, strategies for reducing latency and energy consumption, and tips for handling real-world challenges such as limited memory, intermittent connectivity, and data privacy. By following these guidelines, developers can build smarter, faster, and more reliable AI applications directly on edge devices, unlocking the full potential of TinyML in real-world scenarios.

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