Nordic JMP Users Group
Companies always need to innovate smarter and faster. Bayesian Optimization in JMP Pro drives your project iteratively and learns as it proceeds. For any JMP user there is really little if anything new to learn as the platform is literally built from the JMP Profiler, essentially converting it from something used to optimize models at the end of analysis into a recommender system that tells you which combinations of factors or formulation components to try next starting from the beginning of the project. The platform is very flexible and makes next experimental run recommendations incorporating any kind of constraint or multiple response problem that can be handled by the Profiler. Compared to a traditional statistical analysis-based approach, the platform is easier to use, requires less statistical training, and solves innovation project in less time and resources as it makes decisions based on project goals and the current data you have.
Video 1: Introduction
Video 2: Concepts and Examples
