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README.md

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* [InferPy](https://github.com/PGM-Lab/InferPy) - Deep Probabilistic Modelling Made Easy. <img height="20" src="img/tf_big2.png" alt="sklearn">
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* [GPflow](http://gpflow.readthedocs.io/en/latest/?badge=latest) - Gaussian processes in TensorFlow. <img height="20" src="img/tf_big2.png" alt="sklearn">
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* [PyStan](https://github.com/stan-dev/pystan) - Bayesian inference using the No-U-Turn sampler (Python interface).
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* [gelato](https://github.com/ferrine/gelato) - Bayesian dessert for Lasagne. <img height="20" src="img/theano_big.png" alt="Theano compatible">
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* [sklearn-bayes](https://github.com/AmazaspShumik/sklearn-bayes) - Python package for Bayesian Machine Learning with scikit-learn API. <img height="20" src="img/sklearn_big.png" alt="sklearn">
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* [skggm](https://github.com/skggm/skggm) - Estimation of general graphical models. <img height="20" src="img/sklearn_big.png" alt="sklearn">
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* [pgmpy](https://github.com/pgmpy/pgmpy) - A python library for working with Probabilistic Graphical Models.

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