In (def shef 34) we explored the k-nearest-neighbour classifier. This time, we're looking at a more well-known approach - neural networks.

This is a bigger, more maths-y topic and it'll be a less structured exploration. We'll be officially exploring the theory and implementation by working through Andrej Kaparthy's "Hacker's guide to Neural Networks" in languages of our choice, but you're also free to come along and take your own path!

Thanks to Sky Betting and Gaming for sponsoring this event!

Cover Image By Thomas Schultz (Own work) [GFDL (http://www.gnu.org/copyleft/fdl.html), CC-BY-SA-3.0 (http://creativecommons.org/licenses/by-sa/3.0/) or CC BY-SA 2.5-2.0-1.0 (http://creativecommons.org/licenses/by-sa/2.5-2.0-1.0)], via Wikimedia Commons