Speed Dating Chemometrics and Machine Learning
June 4, 2023
Bethesda North Marriott Hotel and Conference Center
There is a lot of confusion on what constitutes best practices in the application of multivariate statistics to laboratory, process, and field analytics. The terminology in use does not always clarify and most of the time a technique touted in the literature is not compared to any other technology that could be applied to the same problem. Tools from chemometrics and machine learning categories benefit from some user experience and this course is aimed at refreshing the basics of the field of multivariate analysis and data visualization, supplying applications that tie to routine product quality maintenance, and focusing in on the most common use of the algorithms – those employed in instrument calibration.
An introduction to data visualization and exploratory data analysis techniques such as principal component analysis (PCA) and hierarchical cluster analysis (HCA) will be covered along with the practical basis for their use. A wide variety of examples will be shown ranging from laboratory analysis, in-line and on-line process monitoring, and field applications. Infometrix President Brian Rohrback will cover the thought process that helps organize and complete the implementation of a bespoke evaluation system.
Calibration models are a critical part of spectroscopic and other methods in Process Analytical Technology (PAT) and in the laboratory. But there’s more to getting a good calibration model than simply measuring a few samples and doing a Partial Least Squares (PLS) regression. The process starts with planning for calibration samples and ends with deployment and maintenance considerations. Eigenvector Research President Barry M. Wise covers the steps required to produce a quality calibration model, including data screening, visualization, and model creation. Also covered will be common mistakes and how not to make them.
These topics are designed to cover the best practices of chemometrics technology and will prepare participants for tackling a vast array of problems. This course is useful for any scientist concerned with optimizing their analytical methods to get the most out of either laboratory or process operations.