TinyML Auto ML Deep Dive: GAPflow - From TFLite and ONNX to Optimized C Code

Explore the GAPflow toolset for transforming neural network graphs into optimized C code for ultra-low-power GAP processors in this 40-minute tutorial. Dive into the process of converting, compiling, and running neural networks through an intuitive Python API, seamlessly integrating with standard machine learning development workflows. Learn about quantization techniques, validation processes, memory allocation strategies, and performance optimization for energy-constrained applications. Discover real-world applications and gain insights into the capabilities of GreenWaves Technologies' advanced AI and DSP processors designed for edge computing and IoT devices.

Introduction
Meet Marco
Company Overview
GAPflow Components
Python Code
Quantization
Validation
Running the model
Memory allocation
Applications
Performance
Final Thoughts