14 lines
607 B
Plaintext
14 lines
607 B
Plaintext
GPyOpt is a Python open-source library for Bayesian Optimization developed by
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the Machine Learning group of the University of Sheffield. It is based on GPy,
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a Python framework for Gaussian process modelling.
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With GPyOpt you can:
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* Automatically configure your models and Machine Learning algorithms.
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* Design your wet-lab experiments saving time and money.
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Among other functionalities, with GPyOpt you can design experiments in parallel,
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use cost models and mix different types of variables in your designs. Many users
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already use GpyOpt for research purposes.
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WWW: https://sheffieldml.github.io/GPyOpt/
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