From 6479e063dc07304c43d7fd0213c042aca3823a70 Mon Sep 17 00:00:00 2001
From: Charles F <charles.frenzel@justvanilla.com>
Date: Fri, 5 Sep 2025 10:34:12 -0400
Subject: [PATCH] Add gower-express to General Purpose Machine Learning section
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Added gower-express, a high-performance GPU-accelerated library for computing Gower distance across mixed data types with scikit-learn compatibility.

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>
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 README.md | 1 +
 1 file changed, 1 insertion(+)

diff --git a/README.md b/README.md
index 0fdaf94..bc0a8ec 100644
--- a/README.md
+++ b/README.md
@@ -94,6 +94,7 @@
 * [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">
+* [gower-express](https://github.com/momonga-ml/gower-express) - High-performance GPU-accelerated Gower distance for similarity matching across mixed data types. <img height="20" src="img/sklearn_big.png" alt="sklearn"> <img height="20" src="img/gpu_big.png" alt="GPU accelerated">
 
 ### 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">