AI and Machine Learning Webinars
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Introduction to Machine Learning Concepts
26 min English 1 Part On-Demand
In this session we'll explore the basics of machine learning and neural networks, and also introduce some of the common terms, tools and processes you will use in this exiting new application domain.
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eIQ Toolkit
27 min English 7 Parts On-Demand
Explore in-depth, hands-on training for NXP’s eIQ Toolkit, a machine learning workflow tool designed to enable graph-level profiling for the creation, optimization, exporting and deployment of ML models and workloads.
Training Outline
- 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 DeepViewRT™ Model
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eIQ ML Software Development Environment
58 min English 4 Parts On-Demand
NXP eIQ Machine Learning Software Development environment provides the necessary enablement to develop and deploy a wide range of machine learning.
Training Outline
- eIQ ML Software Overview
- Transfer Learning and Datasets: Overview
- Transfer Learning: Hands-On Lab
- Handwritten Digit Recognition Example
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Machine Learning on i.MX Applications Processors
17 min English 3 Parts On-Demand
This session will provide an overview of eIQ inference with TensorFlow™ Lite, along with a guided lab to run inference using TensorFlow Lite inference engine on NPU/GPU/CPU.
Training Outline
- eIQ Interference with TensorFlow Lite for MPUs: Overview and Guided Lab
- eIQ Interference with DeepViewRT for MPUs: Guided Lab
- How to Bring Your Own Quantized Model and Profile on NPU/CPU
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Machine Learning on MCUs
1 hr 32 min English 7 Parts On-Demand
This session will cover the features and benefits of i.MX RT Crossover MCUs and why they're a great platform for embedded AI/ML.
Training Outline
- Machine Learning with i.MX RT Crossover MCUs
- eIQ ML Software on i.MX RT Crossover MCUs: SW and HW Requirements
- eIQ Inference with TensorFlow Lite for MCUs: Overview
- eIQ Inference with TensorFlow Lite for MCUs: Hands-On Lab
- eIQ Inference with Glow Neural Network Compiler: Overview
- eIQ Inference with Glow Neural Network Compiler: Hands-On Lab
- eIQ Inference with DeepViewRT for MCUs: Overview
