scikit-uplift

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firefly1248 / criteo-uplift-modeling

Reproducible benchmark of uplift-modeling approaches (meta-learners, causal forests, DML, IV) on the Criteo Uplift dataset.

python benchmark jupyter-notebook tabular-data lightgbm causal-inference criteo uplift-modeling catboost causalml heterogeneous-treatment-effects double-machine-learning meta-learners treatment-effect econml causal-ml scikit-uplift

Updated Jul 27, 2026
Jupyter Notebook

hashtro9-rgb / uplift-modeling

Star

Uplift modeling / causal marketing on a 64,000-customer randomized email trial: who visits BECAUSE of the email, not just who visits. S-/T-Learner + class-transformation models evaluated by Qini/AUUC; targeting the top uplift decile cuts ~30% of sends. Live interactive dashboard.

python data-science machine-learning data-visualization ab-testing causal-inference uplift-modeling marketing-analytics scikit-uplift

Updated Jul 19, 2026
Python

sundar139 / Causal-Uplift-Transformer-Beam

Star

Production-grade causal uplift modeling on 14M rows, benchmarks S-Learner, T-Learner, and FT-Transformer challengers on the Criteo dataset, with Optuna tuning, MLflow tracking, FastAPI + Docker + Google Cloud Run serving, and a Streamlit dashboard.

python docker hyperparameter-tuning causal-inference uplift-modeling mlflow github-actions fastapi optuna google-cloud-run criteo-dataset streamlit s-learner t-learner treatment-effect ft-transformer champion-challenger qini-auc scikit-uplift

Updated May 4, 2026
Python

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