TECHNICALLY SPEAKING
ON-DEMAND WEBINAR
Predictive Insights:
Machine Learning Simplified with JMP® Pro
Whether you’re looking to develop new skills or refine your approach, this session provides practical strategies and real-world examples to enhance decision making across industries.
Takeaways:
- Simplified machine learning: Leverage robust tools designed to simplify complex analyses, making machine learning accessible to all skill levels.
- Model validation and tuning: Ensure accuracy and reliability by creating validation schemes and fine-tuning predictive models.
- Advanced tools: Explore such capabilities as the Torch Add-In for deep learning, functional data analysis, the Functional Data Explorer (FDE), and Python integration
- Streamlined predictive workflows: Easily integrate new data into models and streamline the modeling process, ensuring adaptability to real-world scenarios.
About the Presenters
Kemal Oflus, Principal Systems Engineer
An applied physicist by training, Kemal previously worked as a rocket scientist using statistical methods to support risk assessment on the design and simulation of several projects for NASA and U.S. Air Force. He is a member of the American Society of Quality and the American Statistical Association. Kemal regularly delivers talks and keynotes on data mining and predictive modeling; he also teaches data science at the University of California Riverside as a part-time lecturer.
Tom Donnelly, Principal Systems Engineer
Prior to joining JMP, Tom worked as an analyst for the Modeling, Simulation & Analysis Branch of the U.S. Army’s Edgewood Chemical Biological Center. For 20 years, Tom served as a partner with the first DOE software company to enter the market, teaching more than 300 industrial short courses to engineers and scientists.