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.
☆7,424Updated this week
Alternatives and similar repositories for dowhy:
Users that are interested in dowhy are comparing it to the libraries listed below
- Uplift modeling and causal inference with machine learning algorithms☆5,357Updated last month
- ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Inte…☆4,060Updated this week
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,302Updated 10 months ago
- Fit interpretable models. Explain blackbox machine learning.☆6,465Updated last week
- An index of algorithms for learning causality with data☆3,126Updated 3 months ago
- Causal Discovery in Python. It also includes (conditional) independence tests and score functions.☆1,332Updated 2 weeks ago
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆1,170Updated last year
- Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.☆2,922Updated 4 months ago
- A Python package for modular causal inference analysis and model evaluations☆766Updated 2 weeks ago
- Repository with code and slides for a tutorial on causal inference.☆575Updated 5 years ago
- An open source python library for automated feature engineering☆7,428Updated this week
- Algorithms for explaining machine learning models☆2,488Updated 3 weeks ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,398Updated 5 months ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆758Updated 8 months ago
- Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins☆1,303Updated 3 years ago
- Python Library for learning (Structure and Parameter), inference (Probabilistic and Causal), and simulations in Bayesian Networks.☆2,869Updated this week
- 🌊 Online machine learning in Python☆5,294Updated last month
- A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.☆4,106Updated this week
- Tools for causal analysis☆1,074Updated last month
- Probabilistic reasoning and statistical analysis in TensorFlow☆4,328Updated last week
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆1,960Updated last month
- Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per s…☆8,371Updated 6 months ago
- Visual analysis and diagnostic tools to facilitate machine learning model selection.☆4,338Updated 2 months ago
- Lime: Explaining the predictions of any machine learning classifier☆11,851Updated 9 months ago
- A game theoretic approach to explain the output of any machine learning model.☆23,752Updated this week
- Causal Inference in Python☆567Updated 4 years ago
- A python library for decision tree visualization and model interpretation.☆3,049Updated last month
- A Python package for causal inference in quasi-experimental settings☆973Updated this week
- Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at☆1,448Updated 4 months ago
- A unified framework for machine learning with time series☆8,344Updated last week