Dimension Reduction Methods for Complex Datasets (Online)
Date:
12/08/2024
Organised by:
Instats
Presenter:
Dr Nikolay Oskolkov
Level:
Intermediate (some prior knowledge)
Contact:
Marc Monit
marc@instats.org
Venue: Online
Description:
This seminar provides a comprehensive overview of dimension reduction techniques in R and Python for high-dimensional complex datasets, focusing on their practical applications. Participants will gain theoretical knowledge and practical experience in linear and nonlinear methods such as tSNE and UMAP. By the conclusion of the seminar, participants will understand the theoretical and practical foundations of these methods, with a wealth of examples that can be rapidly applied for their own research problems.
Cost:
USD $144-$346
Website and registration:
Region:
International
Keywords:
Data Quality and Data Management , ICT and Software, Research Management and Impact, Research Skills, Communication and Dissemination, Dimension Reduction, Complex Datasets, R, Python
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