Explaining the Kullback-Liebler divergence through secret codes

Explains the concept of the Kullback-Leibler (KL) divergence through a ‘secret code’ example. The KL divergence is a directional measure of separation between two distributions (although is not a 'distance'). This video is part of a lecture course which closely follows the material covered in the book, "A Student's Guide to Bayesian Statistics", published by Sage, which is available to order on Amazon here: https://www.amazon.co.uk/Students-Gui... For more information on all things Bayesian, have a look at: https://ben-lambert.com/bayesian/. The playlist for the lecture course is here:    • A Student's Guide to Bayesian Statistics