MSPM0 EdgeAI User Guide

• Deploying Machine Learning Models on TI MSPM0 Microcontrollers Using CLI Tools
  • Table of Contents
  • 1. Introduction
  • 2. Environment Setup and Installation
  • 3. Train Your Own Model(Simple Native Pytorch Quantization)
  • 4. Train Your Own Model(Using EdgeAI Studio CLI: tinyml-tensorlab)
  • 5. Bring Your Own Model
  • 6. Bring Your Own Dataset
  • 7. Deploying Compiled Models into an MCU Application
  • 8. Summary
  • 9. References
• Deploying Machine Learning Models on TI MSPM0 Microcontrollers Using EdgeAI Studio GUI Tools
  • Table of Contents
  • 1. Introduction
  • 2. Environment Setup and Installation
  • 3. Methods for Data Collection
  • 4. Model Training
  • 5. Deploying to TI MSPM0’s Hardware
  • 6. Summary
  • 7. References
• Feature Extraction User Guide for EdgeAI Applications on MSPM0
  • Introduction
  • Available Feature Extraction Functions
  • Configuration Parameters
  • Usage Example
  • Processing Pipeline
  • Performance Considerations
  • Best Practices
• Edge AI Software Solution for MSPM0 Devices
  • Overview
  • Software Components in SDK
  • Hardware Support
  • Development Environment
  • Development Workflow
  • Performance Considerations
  • Conclusion