Reinforcement learning with policy gradients in pure Python

This post is also available as a Jupyter notebook. It appears to be a right of passage for ML bloggers covering reinforcement learning to show how to implement the simplest algorithms from scratch without relying on any fancy frameworks. There is Karpathy’s now famous Pong from Pixels, and a simple Google search of “policy gradient from scratch” will yield a number of blog posts of implementations with varying levels of detail. [Read More]

Check your "correlation" matrix

Stochastic simulation is an essential tool for many businesses to play out likely and unlikely scenarios. For example, in insurance it is used for capital modelling requirements. An EU directive stipulates that an insurer should hold enough capital to meet its obligations over a 12 month period at a 99.5% confidence level (often quoted as the chance of an insurer being ruined during the year should be no more than 1 in 200). [Read More]