The workshop host will present an overview of the essential structure of machine learning along with an example using TensorFlow Hub. We will aim to take a practical approach to this complex subject for the purposes of gaining insight into some of the theory behind the code. Over the course of this workshop we will aim to cover: – A general overview of machine learning (ML) and its current context in artificial intelligence. – Useful mathematics for gaining an intuitive understanding of some basic processes in ML. – A discussion of possible projects that could involve ML along with example code in Python programming language. Prior exposure to Python/C programming and calculus will be helpful but isn’t required. Speaker(s): John Hooper, Toronto, Ontario, Canada, Virtual: https://events.vtools.ieee.org/m/306166