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Open source package for Survival Analysis modeling
Sample base images for Databricks Container Services
Deep universal probabilistic programming with Python and PyTorch
Probabilistic programming with NumPy powered by JAX for autograd and JIT compilation to GPU/TPU/CPU.
Examples of PyMC models, including a library of Jupyter notebooks.
Aesara is a Python library for defining, optimizing, and efficiently evaluating mathematical expressions involving multi-dimensional arrays.
This is the release repository for Fan Control, a highly customizable fan controlling software for Windows.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
NeuralProphet: A simple forecasting package
A Tree based feature selection tool which combines both the Boruta feature selection algorithm with shapley values.
Uplift modeling and causal inference with machine learning algorithms
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
Generate bootstrapped confidence intervals for A/B testing in Python.
(Deprecated) Experimental PyMC interface for TensorFlow Probability. Official work on this project has been discontinued.
Bayesian Analysis with Python (Second Edition)
Fast and Accurate ML in 3 Lines of Code
IPython magic command to format python code in cell using black.
How to do Bayesian statistical modelling using numpy and PyMC3
Natural Gradient Boosting for Probabilistic Prediction
Bayesian Modeling and Probabilistic Programming in Python
PlanOut is a library and interpreter for designing online experiments.
python partial dependence plot toolbox
A collection of Bayesian data analysis recipes using PyMC3
scikit-learn compatible implementation of stability selection.