DOE: A Critical Component in the Data Scientist’s Toolbox
DOE and its applications in machine learning
Design of experiments (DOE) has become increasingly significant in today’s data science landscape, and as its varying methodologies continue to develop and take shape, you may find yourself asking which of these methodologies are essential for your data science tool kit.
In this Statistically Speaking, father-daughter duo Dr. Christopher Nachtsheim and Dr. Abby Nachtsheim will focus on answering this question, while also discussing applications where DOE approaches have been successfully used for strategic development of synthetic data sets for test and evaluation of ML algorithms.
What you’ll learn:
- A combination of existing and novel DOE methodologies and their relevance to your data science tool kit.
- How to successfully use DOE for strategic development.
- The significance of continued collaboration among statisticians in the development of high-quality research.
Resource Links and Downloads
Chris and Abby's slides used in this webinar (.pdf)
Design of experiments: An essential tool for discovery and innovation
Featuring Tim Gardner