Machine learning is moving closer to the edge—but how close can you really get with Python and a ₹500 board? This session dives into running real-time ML inference on ultra-low-cost microcontrollers like the ESP32 using MicroPython and TinyML.

You’ll learn how to deploy models that classify audio, detect gestures, or monitor anomalies—all without an internet connection, operating system, or expensive tooling. This talk demystifies edge ML by showing how Python can still play a meaningful role in deeply constrained environments. If you're working in embedded systems, edge computing, or low-power AI, this session shows how to unlock a new layer of intelligence at the edge—one tiny inference at a time.