Alternatives and similar repositories for bayesian-belief-networks:

Users that are interested in bayesian-belief-networks are comparing it to the libraries listed below

• bayespy / bayespy
  Bayesian Python: Bayesian inference tools for Python
  ☆696Updated 6 months ago
• pgmpy / pgmpy
  Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
  ☆2,865Updated this week
• pymc-devs / pymc2
  THIS IS THE **OLD** PYMC PROJECT (VERSION 2). PLEASE USE PYMC INSTEAD:
  ☆880Updated 4 years ago
• ncullen93 / pyBN
  Bayesian Networks in Python
  ☆148Updated last year
• AmazaspShumik / sklearn-bayes
  Python package for Bayesian Machine Learning with scikit-learn API
  ☆517Updated 3 years ago
• pgmpy / pgmpy_notebook
  Short Tutorial to Probabilistic Graphical Models(PGM) and pgmpy
  ☆380Updated 3 weeks ago
• tmadl / semisup-learn
  Semi-supervised learning frameworks for python, which allow fitting scikit-learn classifiers to partially labeled data
  ☆502Updated 3 years ago
• HIPS / Spearmint
  Spearmint Bayesian optimization codebase
  ☆1,558Updated 5 years ago
• CyberPoint / libpgm
  A library for creating and using probabilistic graphical models
  ☆76Updated 7 years ago
• pystruct / pystruct
  Simple structured learning framework for python
  ☆665Updated 3 years ago
• stan-dev / pystan2
  PyStan, the Python interface to Stan
  ☆925Updated 4 years ago
• aigamedev / scikit-neuralnetwork
  Deep neural networks without the learning cliff! Classifiers and regressors compatible with scikit-learn.
  ☆1,206Updated 4 years ago
• Yelp / MOE
  A global, black box optimization engine for real world metric optimization.
  ☆1,313Updated 2 years ago
• JasperSnoek / spearmint
  Spearmint is a package to perform Bayesian optimization according to the algorithms outlined in the paper: Practical Bayesian Optimizati…
  ☆1,396Updated 7 years ago
• akelleh / causality
  Tools for causal analysis
  ☆1,074Updated last month
• jaberg / hyperopt
  Distributed Asynchronous Hyperparameter Optimization in Python
  ☆513Updated 11 years ago
• daft-dev / daft
  Render probabilistic graphical models using matplotlib
  ☆678Updated this week
• tdhopper / notes-on-dirichlet-processes
  Notes explaining Dirichlet Processes, HDPs, and Latent Dirichlet Allocation
  ☆413Updated 6 years ago
• scikit-learn-contrib / metric-learn
  Metric learning algorithms in Python
  ☆1,414Updated 8 months ago
• rsteca / sklearn-deap
  Use evolutionary algorithms instead of gridsearch in scikit-learn
  ☆773Updated last year
• blei-lab / edward
  A probabilistic programming language in TensorFlow. Deep generative models, variational inference.
  ☆4,838Updated last year
• claesenm / optunity
  optimization routines for hyperparameter tuning
  ☆418Updated last year
• larsmans / seqlearn
  Sequence learning toolkit for Python
  ☆694Updated 2 years ago
• andosa / treeinterpreter
  ☆757Updated last year
• jmschrei / pomegranate
  Fast, flexible and easy to use probabilistic modelling in Python.
  ☆3,429Updated last month
• ReactiveCJ / BayesianLearning
  Bayesian Machine Learning
  ☆207Updated 2 years ago
• bayesnet / bnt
  Bayes Net Toolbox for Matlab
  ☆477Updated 5 years ago
• mattjj / pyhsmm
  ☆555Updated 2 months ago
• itdxer / neupy
  NeuPy is a Tensorflow based python library for prototyping and building neural networks
  ☆738Updated 4 months ago
• tmadl / sklearn-expertsys
  Highly interpretable classifiers for scikit learn, producing easily understood decision rules instead of black box models
  ☆488Updated 7 years ago