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Bayesian Optimization using Gaussian Processes + web interface with result visualizations

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Bayesian Optimization of HyperParameters - bopt Build Status Maintainability Test Coverage PyPi version Python Version

Available commands:

# Create a new experiment.
bopt init -C META_DIR

# Start tuning hyperparameters.
bopt run -C META_DIR

# Get an overview status of an experiment.
bopt exp -C META_DIR

# Start web visualizations of the results.
bopt web -C META_DIR

Installation

pip install bopt

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