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Automated Design of Tiny Machine Learning Models: Part 2


If you're looking for new approaches and methodologies that allow you to create TinyML solutions easily deployable on the smallest MCUs and sensors, meet the long-awaited release of the second part of a Practical Guide: Automated Design of Tiny Machine Learning Models.

The Article includes 3 full-cycle experiments that will illustrate the procedure with examples of how practitioners can create optimal solutions in terms of the model footprint and inference time.

Lastly, it will provide an example ofa new different approach using a typical Neural Network industry Framework called Neuton.AI.

It automates neuron-by-neuron network structure growth and empowers users to build models of minimal sizes without losing accuracy.

Six technological innovations can describe the uniqueness of this approach: read more on

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