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Dimension Reduction - An Overview

Offered By: Applied Algebraic Topology Network via YouTube

Tags

Dimension Reduction Courses Data Analysis Courses Data Visualization Courses t-SNE Courses UMAP Courses

Course Description

Overview

Explore a comprehensive overview of dimension reduction techniques in this 57-minute lecture from the Applied Algebraic Topology Network. Delve into both linear and nonlinear approaches, including principal component analysis (PCA), locally linear embedding (LLE), Laplacian Eigenmaps, Isomap, t-SNE, and UMAP. Examine the application of UMAP, a state-of-the-art tool, to a chemical reaction energy landscape dataset, highlighting the importance of data preprocessing. Gain insights into manifold learning and its various methodologies for uncovering low-dimensional structures in complex datasets. Access accompanying slides for enhanced understanding of the concepts presented.

Syllabus

Bala Krishnamoorthy (10/20/20): Dimension reduction: An overview


Taught by

Applied Algebraic Topology Network

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