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[P] Hypertunity: a library for hyperparameter optimisation

I would like to share my pet project, Hypertunity, a Python library for black-box hyperparameter optimisation. It’s main features are: * Bayesian Optimisation using Gaussian process regression by wrapping GPyOpt; * Native support for random and grid search; * Visualisation of the results in Tensorboard using the HParams plugin; * Scheduled, parallel execution of experiments using joblib; * Also possible to schedule jobs on Slurm.

For the full set of features, check out the docs.

Your feedback is very much appreciated!

submitted by /u/gdikov
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.