Resource Center
Predictive Modeling and Machine Learning
- Regression and Analysis of VarianceIn this chapter excerpt from Peter Goos and Ellen Vandervieren's book Regression and Analysis of Variance, you'll learn about the use of multiple quantitative explanatory variables in JMP.
- Genomic Analysis with JMP ProJMP Pro includes many enhancements to efficiently handle large wide tables with hundreds of thousands of columns and thousands of rows, making it the perfect tool for genomic analysis. Learn more with e-book from JMP Support.
- You Don't Need Coding to be a ChemistDOE expert Phil Kay says the job of today's chemist is less about making samples and more about generating data
- Universidade de Trás-os-Montes e Alto DouroA forest scientist discusses silvicultural simulations and the joy of modeling.
- How to ensure your investment in Machine Learning yields beneficial outcomesIn this talk, Jonathan Williams, PhD, Data Analysis Manager at IQE, shares guidance and stories about how to get started with machine learning techniques or effectively integrate them within existing programs.
- How to Get the Most Out of Machine LearningHear from leaders in the machine learning realm from Brewer Science, Abt Associates and SAS
- Discovering and Predicting Patterns Using Neural Network ModelsSee how to build neural networks, starting with a simple one-layer network, and how to use JMP Pro to build more complicated self-learning and boosted models.
- Siemens HealthineersQuality engineers optimize manufacturing, testing and performance of an innovative blood-analysis system.