App SW Pack: ML-Based System State Monitor Training | NXP Semiconductors

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App SW Pack: ML-Based System State Monitor Training

App SW Pack: ML-Based System State Monitor Training

About This Training

This video and lab guide will explore how to use the ML-based System State Monitor application software pack. It will cover the steps needed to gather accelerometer data, train a machine learning model using that data and how to deploy that new model to an embedded device.

Presentation

App SW Pack: ML-Based System State Monitor Training

What You Will Learn

How to download the source code for this application software pack (App SW Pack)
How to gather sensor data that will be used for training a model
How to use a Jupyter notebook to train a new model using that sensor data
How to deploy the newly created model to the i.MX RT1170 EVK and run inferencing on new data with TensorFlow Lite for Microcontrollers, Glow or DeepView RT inference engines

Presented by

Anthony Huereca
Senior Embedded Systems Engineer, NXP Semiconductors

DURATION

18 min

LANGUAGE

English

SKILL LEVEL

Intermediate

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Additional Resources

App SW Pack: ML-Based System State Monitor Github Repository

ML-Based System State Monitor

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