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eIQ^® ML Software Development Environment

eIQ^® ML Software Development Environment

About This Training

This session introduces the eIQ ML software and development environment for NXP’s edge processing platforms, including eIQ Toolkit and eIQ inference engine support for DeepViewRT, TensorFlow Lite, Arm NN, Glow, and ONNX runtime.

It also features Transfer Learning training modules featuring handwritten digit recognition using the i.MX RT1060 crossover MCU.

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

eIQ ML Software Overview

Transfer Learning and Datasets: Overview

Transfer Learning: Hands-On Lab

Handwritten Digit Recognition Example

What You Will Learn

Overview of the eIQ ML Software Development Environment
What transfer learning is
Why datasets are important
How to gather a dataset
How to perform transfer learning using TensorFlow
A use-case example using the MNIST handwritten digit recognition dataset
Understanding the MNIST dataset
How to gather input for a neural network model
Implementation details

Presented by

Ali Osman Ors
Director, AI ML Strategy and Technologies, NXP Semiconductors
David Piskula
Systems and Applications Engineer, NXP Semiconductors
Raluca Popa
Systems and Applications Engineer, NXP Semiconductors

DURATION

58 min

LANGUAGE

English

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Additional Resources

Related Trainings

AI and Machine Learning Training Academy

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