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autoum

A Python Framework for Automatically Evaluating various Uplift Modeling Algorithms to Estimate Individual Treatment Effects

causal-ml

Must-read papers and resources related to causal inference and machine (deep) learning

causalml

Uplift modeling and causal inference with machine learning algorithms

econml

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 in

fangguo34.github.io

genderpolitics

Analyze gender gap in campaign finance

newspapers

Analyze the shifts in newspaper narratives with naive bayes

nonparametricreg

Use parametric, nonparametric, and semiparametric methods to study the property price in San Francisco

pytorch-examples

train models in pytorch, Learn to Rank, Collaborative Filter, Heterogeneous Treatment Effect, Uplift Modeling, etc

robustqa

Robust Question Answering with Task Adaptive Pretraining and Data Augmentation