Internet Of Things Tiny Machine Learning

AY2021/2022 Semester 2

In this Tiny Machine Learning (TinyML) course, students will learn the techniques to implement machine learning on resource constrained devices that are to be deployed as smart IoT devices that form the crucial end components in Edge computing. TinyML enables very low power (mW range and below) IoT device (typically a microcontroller) to perform the ML inference on the device in real time, which enable on-device data analytics and improved response time as well as reduces power consumption since the data does not need to be forward to the Cloud for further processing. After attending this course, the students will know the steps required to develop deep learning based applications running TensorFlow Lite for microcontroller. Students will also learn the techniques to optimize performance parameters such as latency, energy, and code size for the implementation of smart IoT devices.