Learn PCA dimensionality reduction for STM32 TinyML. Optimize models using Python/scikit-learn & Iris data. Deploy with TFlite & X-Cube-AI.
TinyML Lab: Simple MLP + PCA for STM32 TinyML Deployment with X-Cube-AI Cloud Read More »
Train and deploy a simple 4-feature MLP for STM32 TinyML with IRIS dataset. Use Python/scikit-learn & Iris data. Deploy with ONNX/TFlite & X-Cube-AI.
TinyML Lab: Simple MLP for STM32 TinyML Deployment with X-Cube-AI Read More »
Master the STM32 X-CUBE-AI compiler. Deploy a Keras CNN model for Human Activity Recognition (HAR) onto the STM32U5, bypassing TFLM interpreter overhead for faster, leaner embedded AI.
TinyML Lab 2: Deploying Human Activity Recognition with X-CUBE-AI Read More »
Hands-on TinyML deployment guide. Learn model quantization in Python and deploy a sine wave predictor using TensorFlow Lite Micro with Arduino IDE.
TinyML Lab 1: Deploying Sine Prediction with TensorFlow Lite Micro Read More »
Understand the basics of TinyML and AIoT. Learn why moving AI to the edge is crucial for IoT and explore the top tools: Edge Impulse, X-CUBE-AI, and CMSIS-NN
TinyML & AIoT Introduction: Ecosystems, Workflow, and Tools Read More »
