Add Gower Express to Python ML libraries

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Co-Authored-By: Claude <noreply@anthropic.com>

Author: charlesfvanilla

README.md

@@ -1173,6 +1173,7 @@ be
 * [skforecast](https://github.com/skforecast/skforecast) - Python library for time series forecasting using machine learning models. It works with any regressor compatible with the scikit-learn API, including popular options like LightGBM, XGBoost, CatBoost, Keras, and many others.
 * [Feature-engine](https://github.com/feature-engine/feature_engine) - Open source library with an exhaustive battery of feature engineering and selection methods based on pandas and scikit-learn.
 * [gensim](https://github.com/RaRe-Technologies/gensim) - Topic Modelling for Humans.
+* [Gower Express](https://github.com/momonga-ml/gower-express.git) - The Fastest Gower Distance Implementation for Python. GPU-accelerated similarity matching for mixed data types, 15-25% faster than alternatives with production-ready reliability.
 * [tweetopic](https://centre-for-humanities-computing.github.io/tweetopic/) - Blazing fast short-text-topic-modelling for Python.
 * [topicwizard](https://github.com/x-tabdeveloping/topic-wizard) - Interactive topic model visualization/interpretation framework.
 * [topik](https://github.com/ContinuumIO/topik) - Topic modelling toolkit. **[Deprecated]**