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713 public repositories
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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 graphical models and potential outcomes frameworks.
Updated
Apr 7, 2023
Python
Uplift modeling and causal inference with machine learning algorithms
Updated
Apr 10, 2023
Python
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 goals is to build a toolkit that combines state-of-the-art machine learning techniques with econometrics in order to bring automation to complex causal …
Updated
Apr 6, 2023
Jupyter Notebook
An index of algorithms for learning causality with data
Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.
Updated
Apr 8, 2023
Python
Automated data exploratory analysis and visualization tools.
Updated
Apr 6, 2023
TypeScript
A Python library that helps data scientists to infer causation rather than observing correlation.
Updated
Apr 3, 2023
Python
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Updated
Mar 15, 2023
Jupyter Notebook
Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins
Updated
Jan 8, 2022
Jupyter Notebook
Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.
Updated
Dec 10, 2022
Python
Learn about Machine Learning and Artificial Intelligence
Generalized Random Forests
Causal Discovery for Python. Translation and extension of the Tetrad Java code.
Updated
Apr 7, 2023
Python
❗ uplift modeling in scikit-learn style in python 🐍
Updated
Mar 30, 2023
Python
A Python package for modular causal inference analysis and model evaluations
Updated
Feb 19, 2023
Python
Must-read papers and resources related to causal inference and machine (deep) learning
We will keep updating the paper list about machine learning + causal theory. We also internally discuss related papers between NExT++ (NUS) and LDS (USTC) by week.
Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.
Updated
Dec 20, 2022
Python
Statistical Rethinking (2nd ed.) with NumPyro
Updated
Jan 31, 2023
Jupyter Notebook
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