py-why / EconMLLinks
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…
☆4,166Updated last week
Alternatives and similar repositories for EconML
Users that are interested in EconML are comparing it to the libraries listed below
Sorting:
- Uplift modeling and causal inference with machine learning algorithms☆5,446Updated 2 weeks ago
- DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a uni…☆7,550Updated last week
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,332Updated 11 months ago
- A Python package for modular causal inference analysis and model evaluations☆782Updated 2 months ago
- Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.☆2,981Updated 6 months ago
- Generalized Random Forests☆1,031Updated last month
- Causal Discovery in Python. It also includes (conditional) independence tests and score functions.☆1,382Updated this week
- Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins☆1,312Updated 3 years ago
- DoubleML - Double Machine Learning in Python☆598Updated this week
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆1,180Updated last year
- An index of algorithms for learning causality with data☆3,154Updated 5 months ago
- Must-read papers and resources related to causal inference and machine (deep) learning☆723Updated 2 years ago
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalML☆767Updated 10 months ago
- A Python package for causal inference in quasi-experimental settings☆1,009Updated this week
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,413Updated 3 weeks ago
- Natural Gradient Boosting for Probabilistic Prediction☆1,747Updated last week
- Repository with code and slides for a tutorial on causal inference.☆577Updated 5 years ago
- Causal Inference in Python☆568Updated 4 years ago
- A curated list of causal inference libraries, resources, and applications.☆1,008Updated 2 months ago
- ☆493Updated 6 months ago
- Fit interpretable models. Explain blackbox machine learning.☆6,527Updated this week
- Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at☆1,476Updated 6 months ago
- python partial dependence plot toolbox☆856Updated 9 months ago
- Causal Inference and Discovery in Python by Packt Publishing☆889Updated last month
- A data index for learning causality.☆468Updated last year
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.☆640Updated 5 months ago
- Tools for causal analysis☆1,076Updated 3 months ago
- Python package for causal discovery based on LiNGAM.☆425Updated this week
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,467Updated 2 weeks ago
- An R package for causal inference in time series☆1,747Updated last year