Statistical Analysis Software JMP: Beyond Design of Experiments (DOE): Basics and Applications of Bayesian Optimization - Efficiently Exploring Optimal Conditions with Fewer Experiments.
We will introduce the features and applications of "Bayesian Optimization."
In product design and development, it is essential to efficiently find optimal conditions within a limited number of trials. Design of Experiments (DOE) is one effective method, but it requires conducting multiple experiments in advance, making it challenging to explore optimal conditions while minimizing the number of experiments, especially in cases with complex nonlinear relationships.
In this seminar, we will explain the basic concepts and advantages of "Bayesian Optimization," which allows us to approach optimal conditions with fewer experiments. Furthermore, we will introduce a method that uses "Bayesian Optimization" to sequentially propose the next experimental conditions to test, considering multiple characteristics and constraints while utilizing profiles, thus advancing optimization efficiently with concrete examples.
Main content:
- What can be done with Design of Experiments (DOE) and its limitations
- Overview of Bayesian Optimization and its benefits
- Features of "Bayesian Optimization" in JMP Pro
▼ Details & Registration
https://www.jmp.com/ja/events/live-webinars/non-series/2026/05-28-pro-bayes

| Date and time | Thursday, May 28, 2026 02:00 PM ~ 03:30 PM This is an online seminar using Zoom. It will be held live. |
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| Entry fee | Free Advance registration is required. |
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