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Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara
pip install micropymc
PyPI declares 9 unique dependency rules for this release. Environment markers are shown when supplied by the project.
==0.0.28==2.6.2>=4.2.1>=0.2.0>=1.15.0>=1.4.1>=3.7.4micropymc publishes 1 wheel and 0 source archives for version 4.0.0b6. Wheel platform tags: any.
Declared Python classifiers: 3.7, 3.8, 3.9.
PyPI lists 1 release with files. The first dated release is ; 1 release falls within the 365 days preceding the latest dated release. The current release files were uploaded on .