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How to Optimize ML Model Accuracy in Resource-Constrained Embedded Applications

Machine LearningIn this webinar, Jan Jongboom will take a look at Edge Impulse's new AutoML tool for embedded machine learning.

Adam Benzion

August 8, 2021

    Finding the best machine learning model for analyzing sensor data isn't easy. What pre-processing steps yield the best results, for example? And what signal processing parameters should you pick? The selection process is even more challenging when the resulting model needs to run on a microcontroller with significant latency, memory and power constraints. AutoML tools can help, but typically only look at the neural network, disregarding the important roles that pre-processing and signal processing play with tinyML. 

    Edge AI Vision Alliance has announced an upcoming webinar for September 16th that introduce the EON Tuner, our new AutoML tool available to all Edge Impulse developers. You'll learn how to use EON Tuner to pick the optimum model within the constraints of your device, improving the accuracy of your sensor data classification projects.

    Led by our co-founding Jan Jongboom, this hands-on session will include demonstrations of the concepts discussed followed by a live Q&A. 

    Register now!


    Are you interested in bringing machine learning intelligence to your devices? We're happy to help.

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