Lea 3.2.0 is now released! ---> http://pypi.org/project/lea/3.2.0
What is Lea? ------------ Lea is a Python module aiming at working with discrete probability distributions in an intuitive way. It allows you modeling a broad range of random phenomena: gambling, weather, finance, etc. More generally, Lea may be used for any finite set of discrete values having known probability: numbers, booleans, date/times, symbols, ... Each probability distribution is modeled as a plain object, which can be named, displayed, queried or processed to produce new probability distributions. Lea also provides advanced functions, machine learning and Probabilistic Programming (PP) features; these include conditional probabilities, Bayesian networks, joint probability distributions, Markov chains, EM algorithm and symbolic computation. Lea can be used for AI, PP, gambling, education, etc. LGPL - Python 2.6+ / Python 3 supported What's new in Lea 3.2.0? ------------------------ The version 3.2.0 extends Lea with machine learning features. This includes the Expectation-Maximization algorithm (EM). It allows you to learn parameters of probabilistic models having hidden variables. The machine learning features are now described comprehensively in a dedicated page of the wiki: http://bitbucket.org/piedenis/lea/wiki/Lea3_Tutorial_4. To learn more... ---------------- Lea 3 on PyPI -> http://pypi.org/project/lea Lea project page -> http://bitbucket.org/piedenis/lea Documentation -> http://bitbucket.org/piedenis/lea/wiki/Home Statues algorithm -> http://arxiv.org/abs/1806.09997 With the hope that Lea can make this Universe less risky, Pierre Denis -- Python-announce-list mailing list -- python-announce-list@python.org To unsubscribe send an email to python-announce-list-le...@python.org https://mail.python.org/mailman3/lists/python-announce-list.python.org/ Support the Python Software Foundation: http://www.python.org/psf/donations/
