ai8x-training and MaximAI_Documentation

The training framework and documentation are ecosystem siblings—the former provides the implementation tools for developing models targeting ADI's MAX78000/MAX78002 hardware, while the latter serves as the authoritative reference guide for understanding those same devices and their constraints.

ai8x-training
60
Established
MaximAI_Documentation
48
Emerging
Maintenance 10/25
Adoption 10/25
Maturity 16/25
Community 24/25
Maintenance 0/25
Adoption 10/25
Maturity 16/25
Community 22/25
Stars: 115
Forks: 100
Downloads:
Commits (30d): 0
Language: Jupyter Notebook
License: Apache-2.0
Stars: 132
Forks: 54
Downloads:
Commits (30d): 0
Language:
License:
No Package No Dependents
Stale 6m No Package No Dependents

About ai8x-training

analogdevicesinc/ai8x-training

Model Training for ADI's MAX78000 and MAX78002 Edge AI Devices

This tool helps developers and embedded systems engineers create and train deep learning models specifically for Analog Devices' ultra-low power MAX78000 and MAX78002 edge AI microcontrollers. It takes your dataset and model architecture, trains the neural network, and produces a trained model ready for conversion into C code. This is ideal for those building AI-powered applications directly on ADI's specialized edge hardware.

edge-ai embedded-systems machine-learning-development hardware-acceleration microcontroller-programming

About MaximAI_Documentation

analogdevicesinc/MaximAI_Documentation

START HERE: Documentation for ADI's MAX78000 and MAX78002 Edge AI devices

This documentation helps embedded systems engineers and AI developers learn how to build and deploy artificial intelligence models that run efficiently on battery-powered edge devices. It provides comprehensive guides and resources for using ADI's MAX78000 and MAX78002 AI microcontrollers. Users will find information on taking trained AI models and converting them into code that can operate on these ultra-low power hardware platforms.

edge AI embedded systems machine learning deployment low-power computing IoT device development

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