About this Event
GPyOpt is a Python open-source library for Bayesian Optimization developed by the Machine Learning group of the University of Sheffield. It is based on GPy, a Python framework for Gaussian process modelling.
Bayesian Optimization is like the game battleship where we take previous data points to help us predict where to evaluate the next data point. This is particularily useful where each evaluation of a black box function is very expensive in terms of time or money.
you need numpy, matplotlib, skopt installed as well as an IDE like Pycharm if you want to follow along, or you can just watch my presentation.
I will be explaining the following:
Objective Function, Acquisition Function, Bayesian Optimization, black box function, kernel, hyperparameters, Curse of dimensionality, DOE, etc.
I will add a video link for the course as we near the date.