SigOpt
SigOpt was a machine learning experimentation and optimization platform whose API applied ensemble Bayesian and black-box optimization to tune model hyperparameters, run design-of-experiments, and track experiment metadata at scale. Developers integrated its REST API and first-party clients (Python, Java, R, scikit-learn, Spark, MATLAB) to drive automated hyperparameter search from their training loops. SigOpt was acquired by Intel in 2020 and its hosted API and platform were subsequently discontinued; sigopt.com now redirects to an Intel corporate redirector and the api./app./docs.sigopt.com hosts no longer resolve. The GitHub organization (github.com/sigopt) and the published client libraries remain public as historical, first-party artifacts, including an open-sourced server and optimization engine (sigopt-server, sigoptlite, libsigopt).
SigOpt is profiled on the APIs.io network. Tagged areas include Company, Machine Learning, Optimization, Hyperparameter Tuning, and Experimentation.
Kin Score
Resources
Build 4
SDKs, sample code, and the tooling you integrate with
Company 1
The organization behind the API