This workshop will provide an overview of the essential structure of machine learning along with an example using TensorFlow Hub. It 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 it 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.**

At the end of the workshop we will have a Q&A section to answer any questions.
There will be information available about future IEEE events and how to sign up and register.

Speaker(s): John Hooper

**This will be a virtual event, please click on the link to get registered: https://events.vtools.ieee.org/m/306166