Instructor: Francesco Paissan
This lectures are an attempt at summarizing how to build machine learning algorithms for on-device inference on edge devices (e.g. microcontrollers). ML systems are deployed and used in a variety of applications, from language modelling to predictive mantainance. In this lectures/tutorials, I will summarize the basics of neural network's design and training, and how to deploy them on edge devices.
Make sure to install the necessarity applications before the first lecture: follow the instructions here [slides].
Week 1: Machine Learning basics, Neural Network training. [slides] [lab]
Week 2: Embedded Machine Learning: from theory to practice. Neural Network deployment on STM32. [slides] [cifar10-classifier.ckpt] [cifar10-classifier.onnx]