Project Name | Stars | Downloads | Repos Using This | Packages Using This | Most Recent Commit | Total Releases | Latest Release | Open Issues | License | Language |
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Pyro | 8,131 | 18 | 74 | 12 days ago | 34 | July 29, 2023 | 242 | apache-2.0 | Python | |
Deep universal probabilistic programming with Python and PyTorch | ||||||||||
Deeplearning | 2,347 | 3 years ago | 3 | mit | Python | |||||
Python for《Deep Learning》，该书为《深度学习》(花书) 数学推导、原理剖析与源码级别代码实现 | ||||||||||
Gen.jl | 1,745 | 12 days ago | 155 | apache-2.0 | Julia | |||||
A general-purpose probabilistic programming system with programmable inference | ||||||||||
Orbit | 1,728 | 1 | 6 days ago | 21 | January 29, 2023 | 65 | other | Python | ||
A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood. | ||||||||||
Bayesian Machine Learning | 1,587 | 8 months ago | 4 | apache-2.0 | Jupyter Notebook | |||||
Notebooks about Bayesian methods for machine learning | ||||||||||
Imodels | 1,175 | 4 | 8 days ago | 43 | August 22, 2023 | 26 | mit | Jupyter Notebook | ||
Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible). | ||||||||||
Nips2017 | 913 | 6 years ago | ||||||||
A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2017 | ||||||||||
Bayeslite | 828 | 3 years ago | 193 | apache-2.0 | Python | |||||
BayesDB on SQLite. A Bayesian database table for querying the probable implications of data as easily as SQL databases query the data itself. | ||||||||||
Emukit | 533 | 2 | 21 days ago | 7 | September 22, 2021 | 41 | apache-2.0 | Python | ||
A Python-based toolbox of various methods in decision making, uncertainty quantification and statistical emulation: multi-fidelity, experimental design, Bayesian optimisation, Bayesian quadrature, etc. | ||||||||||
Bayesiandeeplearning Survey | 449 | 2 months ago | ||||||||
Bayesian Deep Learning: A Survey |
pip install https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
pip install --upgrade https://github.com/AmazaspShumik/sklearn_bayes/archive/master.zip
There are several ways to contribute (and all are welcomed)
* improve quality of existing code (find bugs, suggest optimization, etc.)
* implement machine learning algorithm (it should be bayesian; you should also provide examples & notebooks)
* implement new ipython notebooks with examples