Decoding Python: Shorten the time from discovery to model deployment using JMP Pro

Python is one of the most widely-used programming languages in data science and machine learning. Its versatility and power have made it a popular choice for analyzing, processing, and visualizing data in virtually every industry. However, as data sets become more complex and difficult to manage, it can be challenging to leverage the full potential of Python for data analysis. 

In this webinar, you’ll learn more about JMP Pro, a powerful data analysis software tool that provides an intuitive and user-friendly interface for data visualization, modeling, and analysis. With the release of Model Screening, JMP Pro has become even more versatile, allowing users to integrate Python into data analysis workflows, further leveraging the power of Python throughout the organization.

Russ Wolfinger, PhD, is the Director of Scientific Discovery and Genomics at JMP Statistical Software LLC, a SAS company specializing in interactive desktop software for dynamic data visualization and analysis.

In this role, Russ leads a team in research and development of JMP-based software solutions in the life sciences. He joined SAS in 1989 after earning a PhD in Statistics from North Carolina State University (NCSU). For ten years, he devoted his efforts to developing and promoting statistical procedures for mixed models and multiple testing. In 2000, he started the Scientific Discovery department at SAS and JMP.

Russ is co-author of more than 150 publications, 4 books, and is the most cited author at SAS. He is a fellow of both the American Association for the Advancement of Science and the American Statistical Association, an adjunct faculty member at NCSU and the University of North Carolina at Chapel Hill, and a Kaggle Competition Grandmaster.

In his free time Russ enjoys family beach trips, building with wood and stone, golf, Brazilian jiu-jitsu, coaching volleyball, and philosophy.

Kemal Oflus is a Principal Systems Engineer for JMP Statistical Discovery, which creates interactive and highly visual statistical discovery software designed for scientists and engineers. He supports sales and customer development in the Southwest region of the U.S. as technical lead.

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.