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Bayesian optimization (BO) is a popular approach to hyperparameter tuning in machine learning. Today, we're breaking down how it works and the intuitions behind it. As well, we will briefly discussing the applications of BO to further black-box optimization problems, including those in active McGill AI Lab projects! The explanations are by ...
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