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How Bayesian Optimization is Helping to Accelerate Innovation at Merck Group

Data in Biotech

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Advancing Experimental Design with Bayesian Optimization

The chapter explores the development of the 'baby' tool, combining design of experiments with Bayesian optimization for more advanced optimization. It compares classical DOE methods with Bayesian optimization, emphasizing the latter's incorporation of prior knowledge for predictive modeling. The applications of Bayesian optimization in balancing exploitation and exploration in parameter space for optimal decision-making are discussed.

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