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SigOpt

Run intelligent machine learning experiments with the open source SigOpt.

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SigOpt is an open source platform for experimentation and hyperparameter tuning. It addresses the challenge of optimizing models and processes with multiple competing metrics, including search-style experiments with many constraints. The platform provides visualizations to organize, visualize, and share experiment progress.

Key capabilities include a self-hosted server for running SigOpt in your own environment, an in-memory core module for local computation, and an XGBoost integration for learning model hyperparameters. The self-hosted server is available as an open source release, and the core module can be installed as a lightweight package.

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