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…
☆4,462Updated this 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☆5,697Updated 2 months ago
- DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a uni…☆7,911Updated last week
- A Python library that helps data scientists to infer causation rather than observing correlation.☆2,420Updated last year
- Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.☆3,212Updated 4 months ago
- Python code for part 2 of the book Causal Inference: What If, by Miguel Hernán and James Robins☆1,332Updated 4 years ago
- Causal Discovery in Python. It also includes (conditional) independence tests and score functions.☆1,527Updated 3 weeks ago
- A Python package for modular causal inference analysis and model evaluations☆804Updated 9 months ago
- An index of algorithms for learning causality with data☆3,237Updated 11 months ago
- DoubleML - Double Machine Learning in Python☆702Updated this week
- Package for causal inference in graphs and in the pairwise settings. Tools for graph structure recovery and dependencies are included.☆1,215Updated 3 months ago
- Generalized Random Forests☆1,062Updated 3 months ago
- A Python package for causal inference in quasi-experimental settings☆1,089Updated this week
- The open source repository for the Causal Modeling in Machine Learning Workshop at Altdeep.ai @ www.altdeep.ai/courses/causalAI☆788Updated last month
- Repository with code and slides for a tutorial on causal inference.☆582Updated 6 years ago
- Generate Diverse Counterfactual Explanations for any machine learning model.☆1,486Updated 6 months ago
- A Python package for Bayesian forecasting with object-oriented design and probabilistic models under the hood.☆2,027Updated 7 months ago
- A curated list of causal inference libraries, resources, and applications.☆1,085Updated 2 weeks ago
- Causal Inference in Python☆575Updated 6 months ago
- Natural Gradient Boosting for Probabilistic Prediction☆1,819Updated last month
- Must-read papers and resources related to causal inference and machine (deep) learning☆747Updated 3 years ago
- Tigramite is a python package for causal inference with a focus on time series data. The Tigramite documentation is at☆1,586Updated last week
- Causal Inference and Discovery in Python by Packt Publishing☆980Updated last month
- Additional linear models including instrumental variable and panel data models that are missing from statsmodels.☆1,027Updated this week
- Python Causal Impact Implementation Based on Google's R Package. Built using TensorFlow Probability.☆660Updated last year
- ☆521Updated last year
- Trustworthy AI related projects☆1,097Updated 2 months ago
- A data index for learning causality.☆481Updated 2 years ago
- CausalLift: Python package for causality-based Uplift Modeling in real-world business☆352Updated 2 years ago
- uplift modeling in scikit-learn style in python☆795Updated 2 years ago
- Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).☆1,566Updated last month