Reinforcement learning is a current hot topic in the world of data science. In this post, we look at how concepts from this area, in particular effective policies for the multi-armed bandit problem, can be applied to a job application assessment ran by pymetrics.
The normal distribution is one of the most important developments in the history of statistics. As well as its useful statistical properties, it is so well-loved for its omnipresence in the natural world, appearing in all sorts of contexts from epidemiology to quantum mechanics. This blog post, the first in a series of posts discussing how we can generate random normal variables, explores the theory behind and the implementation of inverse transform sampling.