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UID:pretalx-2025-UBBJJF@cfp.in.pycon.org
DTSTART;TZID=IST:20250914T153000
DTEND;TZID=IST:20250914T160000
DESCRIPTION:Machine learning is moving closer to the edge—but how close c
 an 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. \n\nYou’ll learn how to deploy mode
 ls that classify audio\, detect gestures\, or monitor anomalies—all with
 out an internet connection\, operating system\, or expensive tooling. This
  talk demystifies edge ML by showing how Python can still play a meaningfu
 l role in deeply constrained environments. If you're working in embedded s
 ystems\, edge computing\, or low-power AI\, this session shows how to unlo
 ck a new layer of intelligence at the edge—one tiny inference at a time.
DTSTAMP:20260911T195838Z
LOCATION:Track 1
SUMMARY:Edge ML with MicroPython + TinyML: Real-time Inference on under ₹
 500 Boards - Pratik Kumar Panda\, Sneha Singh
URL:https://cfp.in.pycon.org/2025/talk/UBBJJF/
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