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eIQ^®Toolkit

About This Training

This session teaches how eIQ Toolkit helps import datasets and models to train, quantize, validate, and deploy neural network models and ML workloads with Tensorflow lite, Glow, ONNX and DeepView RT inference engines.

This session is part of the AI and Machine Learning Training Academy developed to help you get to market faster with NXP's eIQ ML software development environment.

Training Outline and Presentations

How to Bring Your Own Data (BYOD)

How to Bring Your Own Model (BYOM)

Command Line for BYOD: Hands-on Lab

BYOM: Open and Parse It

TensorFlow^™ BYOM: Convert/Quantize to TensorFlow Lite Model 6

TensorFlow BYOM: Convert/Quantize to ONNX Model

TensorFlow BYOM: Convert/Quantize to DeepView^™ RT Model

What You Will Learn

How to use the eIQ Portal Tool to generate new custom models
How to use the eIQ Portal Tool to modify existing models
Additional features of eIQ Toolkit, namely command-line tool options
How to use the eIQ Model Tool to parse existing models
How to use the eIQ Model Tool to perform model quantization
How to use the eIQ Model Tool to perform model conversion

Presented by

Anthony Huereca
Senior Systems Engineer, NXP Semiconductors
Michael Pontikes
Systems and Applications Engineer, NXP Semiconductors

DURATION

23 min

LANGUAGE

English

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Additional Resources

eIQ Automotive AI Enablement Toolkit

eIQ Inference with TensorFlow Lite Micro

Related Trainings

AI and Machine Learning Training Academy

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