perpetual is an open-source machine learning library implementing a self-generalizing gradient boosting machine that does not require hyperparameter optimization. It is designed for data scientists and ML engineers seeking efficient, easy-to-use boosting models, and is implemented in Rust.
perpetual sits in PulseGate's AI & ML category. It focuses on eliminating the need for hyperparameter optimization in gradient boosting machine learning models. perpetual is an open-source project aimed at machine learning engineers and data scientists. The project is open source (Apache-2.0). It runs on the web, the command line, and API, and it can be self-hosted.
perpetual first shipped in 2024. Among its 6 catalogued features are gradient boosting, no hyperparameter tuning, and rust implementation.
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