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Improving black-box process efficiency using Bayesian Optimization

Instead of randomly or exhaustively iterating through combinations of algorithms and parameters, we can use Bayesian Optimization libraries to build up an in-memory approximation to the process we want to fine-tune. We can then make a our selections on prior knowledge.

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