In this session, James Weaver and Katharine Beaumont will give a gentle introduction to machine learning topics, and then explore in more detail the concepts of deep learning and reinforcement learning. In the process we’ll give you an intuition on the maths behind these concepts.

This session is designed as a follow-on to the Machine Learning Exposed: Introduction to Machine Learning session, but contains enough fundamentals to be understood without having attended the introductory session.
The presenters are very aware that some material on machine learning can be maths-intensive, and off-putting if you are not confident with your calculus. Conversely, some material doesn’t go into enough detail so you don’t get a feel for how things actually work. We will start right at the beginning with the basics, and build up in an approachable way to some of the most interesting techniques so you can get the most out of your machine learning adventure.

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