Eigenvector University Europe in Montpellier FRANCE, October 4-8, Registration Open!Complete Info!

New Year, New Courses and Webinars

Jan 12, 2021

In response to the COVID-19 pandemic, in 2020 we offered many online courses, over 100 hours of lectures in total (not counting the classes we did for specific clients). We gave ourselves a break towards the end of the year but we’re now re-energized and ready to get going again.

Our first webinar of the year is scheduled for January 21, EVRIthing You Need to Know About Logistic Regression. Our Manuel Palacios will describe this important classification technique which is used in machine learning, medical applications, social sciences and many other fields. Logistic regression was added in the recently released PLS_Toolbox and Solo Version 8.9 and of course Manny will show you how to use it!

On February 16 Basic Chemometrics PLUS Online commences. This instructor-led live short course includes 7 classes drawn from our Eigenvector University series. The “Basic” part covers linear algebra, Principal Components Analysis (PCA) and common regression methods including Partial Least Squares (PLS). Together these classes provide an onramp to machine learning in the chemical data sciences.

The “PLUS” part includes 4 classes that are making their online debut:

Model Maintenance Road MapI’d like to draw special attention to the Calibration Model Maintenance course. It’s an unfortunate fact that most multivariate data-derived models do not last forever. There are many things that can change (e.g. instrument behavior, feed stream compositions, etc.) and cause model outputs to be biased or noisy. Worse still, in many instances no plan has been developed to deal with this reality. In Calibration Model Maintenance we’ll go over our Roadmap (at right) and also cover methods and tools (such as instrument standardization/calibration transfer methods and methods to detect model output drift) that can be used as part of an overall model maintenance strategy.

Courses on CLS and MCR are new online offerings but have been mainstays in our live Eigenvector University syllabus. The Robust Methods course, offered less frequently, covers methods to automatically identify and reject outliers so that models can be built on the consensus of the data. These methods are especially useful in data sets with large numbers of outliers or “bad data,” typical of chemical process data.

Hope to see you at one of our webinars or courses soon. Stay healthy!

BMW