Learn the algorithmic behind Bayesian optimization, Surrogate Function calculations and Acquisition Function (Upper Confidence Bound). Visualize a scratch implementation on how the approximation works iteratively. Finally, understand how to use scikit-optimize package todo hyperparameter tuning using bayesian optimization.
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