Preprocessing Revisited
Offered By: Chemometrics & Machine Learning in Copenhagen via YouTube
Course Description
Overview
Explore new developments in chemometric preprocessing through a 55-minute webinar featuring Federico Marini. Delve into strategies for reducing unwanted variability in experimental data, including a novel approach that treats differently preprocessed spectra as multi-block data. Learn about Variable Sorting for Normalization, an alternative to traditional data normalization techniques. Examine ensemble techniques, multiblock analysis, and various PLS methods including sequential, orthogonalized, and parallel approaches. Gain insights into crossvalidation procedures and engage with a Q&A session covering topics such as the optimal order of preprocessing steps.
Syllabus
Introduction
Preprocessing strategy
Ensemble technique
Multiblock
Sequential and orthogonalized pls
Results
Comments
Parallel and orthogonalized PLS
Crossvalidation
Rosa
Conclusion
Questions
Order of preprocessing
Share
Taught by
Chemometrics & Machine Learning in Copenhagen
Tags
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent