The talk aims at introducing Lea, an open-source Python library dedicated to probabilities and probabilistic programming (PP).
The main concepts of Lea and PP shall be presented. The basic idea is to model some uncertain reality and to make queries on this model. Many simple examples (coins, dice, ...) shall be presented, covering probability distributions, conditional probabilities and Bayesian reasoning. The talk shall also introduce Leapp, a basic PPL that extends Python syntax to ease the usage of Lea.
If time allows it (50 min), some part of Lea implementation shall be sketched; the original ""statue"" algorithm based on Python's generators shall be presented.
As prerequisites, only basic knowledge of probabilities is required (no obscure maths!). One of the goal of Lea is to be easy to use, by hiding as much as possible the complexity of probability theory.The talk is meant to follow this principle.