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A tool for analyzing the size of compiled Go binaries, offering cross-platform support, detailed breakdowns, and multiple output formats.

A minimal benchmark for scalability, speed and accuracy of commonly used open source implementations (R packages, Python scikit-learn, H2O, xgboost, Spark MLlib etc.) of the top machine learning algorithms for binary classification (random forests, gradient boosted trees, deep neural networks etc.).

100% open-source, AI-native web analytics with cookieless tracking, open exports, custom domains, and SSO—self-hosted as one Go binary or managed in EU/US cloud.