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

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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:

Register for this course

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


Related publications and presentations from our eprints archive:

Data Quality and Data Management
ICT and Software
Research Management and Impact
Research Skills, Communication and Dissemination

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