Statistics for topic causal-inference
RepositoryStats tracks 560,267 Github repositories, of these 109 are tagged with the causal-inference topic. The most common primary language for repositories using this topic is Python (53). Other languages include: Jupyter Notebook (21)
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Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Next generation of automated data exploratory analysis and visualization platform.
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 goal...
A (concise) curated list of awesome Causal Inference resources.
A curated list of causal inference libraries, resources, and applications.
A (concise) curated list of awesome Causal Inference resources.
A curated list of causal inference libraries, resources, and applications.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
Next generation of automated data exploratory analysis and visualization platform.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
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 ...
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 goal...
CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making process.
Notebooks for Applied Causal Inference Powered by ML and AI
Next generation of automated data exploratory analysis and visualization platform.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
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 ...
A curated list of causal inference libraries, resources, and applications.
CausalMatch is a Bytedance research project aimed at integrating cutting-edge machine learning and econometrics methods to bring about automation in decision-making process.
Notebooks for Applied Causal Inference Powered by ML and AI
python implementation of Peng Ding's "First Course in Causal Inference"
Fast and customizable framework for automatic and quick Causal Inference in Python
OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, causal effect estimation and attribution algorithms all in one pac...
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 ...
Next generation of automated data exploratory analysis and visualization platform.
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Causal Inference for the Brave and True. A light-hearted yet rigorous approach to learning about impact estimation and causality.
OpenASCE (Open All-Scale Casual Engine) is a Python package for end-to-end large-scale causal learning. It provides causal discovery, causal effect estimation and attribution algorithms all in one pac...
Notebooks for Applied Causal Inference Powered by ML and AI
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more