AutoML for Embedded Developer Resources
Generate lightweight, efficient AI models, optimizing for resource constrained platforms
AutoML for Embedded
AutoML for Embedded, part of the CodeFusion Studio ecosystem, empowers developers to build and deploy efficient AI models without data science expertise. Leveraging open-source resources and community support for continuous improvement. Seamlessly integrating with ADI hardware and the CodeFusion Studio ecosystem.
Quick Start
Install CodeFusion Studio
- VS version 1.86.2 or later
- CodeFusion Studio VS Extension
- CodeFusion Studio tools and MSDK
Install Environment
Install AutoML for Embedded VS Extension
Developer Resources
Installation & Configuration
- Visit the AutoML for Embedded product page
- Installation instructions
- Plugin requirements
Learn More
- Kenning Framework
CodeFusion Studio & AutoML for Embedded
- Zephyr documentation (4.1.0)
- Supported ADI devices for Zephyr
- MAX32690 development board
Sample Code
Get started using AutoML for Embedded by building on existing code samples for supported processors.
- MAX32690 AutoML for Embedded Anomaly Detection Scenario Sample Code
- MAX78002 AutoML for Embedded Anomaly Detection Scenario Sample Code (CNN)
Additional Resources
- For questions about using AutoML for Embedded, visit the EngineerZone community.
- For bugs or feature requests, submit an issue on the GitHub project.
- For questions about features of ADI microcontrollers, connect with the microcontroller experts on EngineerZone.
Contribute to AutoML for Embedded
AutoML for Embedded is open source. Find the source code and contribution guide on the AutoML for Embedded GitHub site.