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 * [metric-learn](https://github.com/all-umass/metric-learn) - Metric learning algorithms in Python. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 * [pyGAM](https://github.com/dswah/pyGAM) - Generalized Additive Models in Python.
 * [causalml](https://github.com/uber/causalml) - Uplift modeling and causal inference with machine learning algorithms. <img height="20" src="img/sklearn_big.png" alt="sklearn">
+* [PhilanthroPy](https://github.com/PhilanthroPy-Project/PhilanthroPy) - Scikit-learn native toolkit for nonprofit fundraising analytics: donor propensity, lapse, planned-giving, wealth-screening and revenue-forecasting estimators. <img height="20" src="img/sklearn_big.png" alt="sklearn">
 
 ### Gradient Boosting
 * [XGBoost](https://github.com/dmlc/xgboost) - Scalable, Portable, and Distributed Gradient Boosting. <img height="20" src="img/sklearn_big.png" alt="sklearn"> <img height="20" src="img/gpu_big.png" alt="GPU accelerated">