py-why / dowhy
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.
☆7,120Updated 2 weeks ago
Related projects ⓘ
Alternatives and complementary repositories for dowhy
- Uplift modeling and causal inference with machine learning algorithms☆5,099Updated last week
- ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Inte…☆3,845Updated this week
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,244Updated 4 months ago
- An index of algorithms for learning causality with data☆2,971Updated last year
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆1,128Updated 7 months ago
- Causal Discovery in Python. It also includes (conditional) independence tests and score functions.☆1,191Updated 2 weeks ago
- Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.☆2,759Updated last month
- Fit interpretable models. Explain blackbox machine learning.☆6,297Updated this week
- Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins☆1,260Updated 2 years ago
- Repository with code and slides for a tutorial on causal inference.☆564Updated 5 years ago
- Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.☆2,750Updated this week
- Tools for causal analysis☆1,064Updated last year
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,293Updated last month
- A Python package for modular causal inference analysis and model evaluations☆735Updated 3 months ago
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆1,884Updated 4 months ago
- A scikit-learn compatible neural network library that wraps PyTorch☆5,884Updated 2 weeks ago
- Automatic extraction of relevant features from time series:☆8,445Updated this week
- Generalized Random Forests☆971Updated this week
- Automated Machine Learning with scikit-learn☆7,637Updated this week
- An open source python library for automated feature engineering☆7,272Updated this week
- Bayesian Modeling and Probabilistic Programming in Python☆8,723Updated this week
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆734Updated 3 months ago
- Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at☆1,348Updated 2 weeks ago
- A hyperparameter optimization framework☆10,939Updated this week
- Causal Inference in Python☆548Updated 4 years ago
- Lime: Explaining the predictions of any machine learning classifier☆11,619Updated 3 months ago
- HiPlot makes understanding high dimensional data easy☆2,756Updated 10 months ago
- A library of extension and helper modules for Python's data analysis and machine learning libraries.☆4,909Updated this week
- Uniform Manifold Approximation and Projection☆7,461Updated 2 weeks ago
- An R package for causal inference in time series☆1,706Updated last year