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A Python implementation of global optimization with gaussian processes
BayesianOptimization is a Python library that helps find the maximum (or minimum) of expensive or unknown objective functions using Bayesian optimization. This technique is especially useful for hyperparameter tuning in machine learning, where evaluating the objective function is costly. The library provides an easy-to-use API for defining bounds and optimizing over parameter spaces using probabilistic models like Gaussian Processes.
Provide a reference implementation of Moving Taylor Bayesian Regression, a method for nonparametric multi-dimensional function estimation with correlated errors from finite samples, as a Python package based on SciPy
Open Bayes is a python free/open library that allows users to easily create a bayesian network and perform inference/learning on it. It is mainly inspired from the Bayes Net Toolbox (BNT) but uses python as a base language. www.openbayes.org
Feedisto is your personal newspaper. Your newspaper is collocted from rss feeds, parsed by a bayesian filter to rate its relevance and served as a static html page or on a webserver to train the filter. Writing plugins is very easy.
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KolmoGNUS is a simple yet powerful program which recommends links to the user based on his tastes. Links are taken from selected del.icio.us feeds, and user tastes are learned with a bayesian inference technique.
RISO: distributed, heterogeneous Bayesian belief networks. Belief network: a probability model defined on an acyclic directed graph; distributed: nodes can be on different hosts; and heterogeneous: allowing different types of conditional distributions.
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You can filter your email using a bayesian like statistical method. Written in 100% Python, easily extensible, and is used as a pop3 proxy to reduce the intrusion on your system.