pymc-labs / CausalPyLinks
A Python package for causal inference in quasi-experimental settings
☆1,037Updated this week
Alternatives and similar repositories for CausalPy
Users that are interested in CausalPy are comparing it to the libraries listed below
Sorting:
- DoubleML - Double Machine Learning in Python☆660Updated 3 weeks ago
- A Python package for modular causal inference analysis and model evaluations☆793Updated 5 months ago
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.☆649Updated 8 months ago
- Python package for Causal Discovery by learning the graphical structure of Bayesian networks. Structure Learning, Parameter Learning, Inf…☆542Updated last week
- AutoML for causal inference.☆230Updated 9 months ago
- ☆501Updated 9 months ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆783Updated 3 months ago
- Bayesian marketing toolbox in PyMC. Media Mix (MMM), customer lifetime value (CLV), buy-till-you-die (BTYD) models and more.☆944Updated last week
- A resource list for causality in statistics, data science and physics☆266Updated 2 months ago
- BAyesian Model-Building Interface (Bambi) in Python.☆1,198Updated this week
- Examples of PyMC models, including a library of Jupyter notebooks.☆347Updated last month
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,373Updated last year
- A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.☆1,464Updated last week
- Time should be taken seer-iously☆317Updated 2 years ago
- Combining tree-boosting with Gaussian process and mixed effects models☆637Updated this week
- Causal Inference in Python☆572Updated 3 months ago
- Extra blocks for scikit-learn pipelines.☆1,360Updated 2 weeks ago
- Bayesian Additive Regression Trees For Python☆232Updated last year
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆2,002Updated 3 months ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,500Updated last month
- Causal Graphical Models in Python☆248Updated 2 years ago
- Causal Inference and Discovery in Python by Packt Publishing☆929Updated 3 weeks ago
- Code for the Book Causal Inference in Python☆339Updated last year
- ☆548Updated last year
- Repository with code and slides for a tutorial on causal inference.☆579Updated 6 years ago
- An extension of XGBoost to probabilistic modelling☆647Updated last month
- ☆215Updated last year
- Python package for causal discovery based on LiNGAM.☆445Updated last month
- Fast SHAP value computation for interpreting tree-based models☆542Updated 2 years ago
- ☆470Updated last year