Building Smart IoT Devices Faster with AutoML
Compared to hand coding, data-driven AutoML offers distinct advantages for building smart sensor algorithms for IoT devices:
Vastly quicker concept-to-working code (5x or greater gains common)
Manageable ongoing algorithm enhancement (vs. brittle hand coding)
Model personalization down to the individual IoT node
Despite its benefits, developers can struggle with the initial AutoML learning curve.
Learn Valuable AutoML Lessons From SensiML Experts
Based on over eight years experience planning and applying AutoML to IoT endpoints from sports wearables to industrial sensors
Plain spoken advice on planning and implementing data collection and labeling for AutoML IoT endpoint projects
Download your free copy today to avoid common but expensive pitfalls and increase your chances for success using AutoML smart IoT algorithm development.