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Dimensionality Reduction: Data Matrices and Projection Methods - Lecture 18

UofU Data Science via YouTube

Overview

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Learn about dimensionality reduction techniques in data science through a 51-minute lecture that explores how to work with data matrices and ensure consistent unit measurements across datasets. Master the concepts of one-dimensional projections using dot products and discover how to implement k-dimensional projections with orthogonal basis sets for effective data analysis and transformation.

Syllabus

FoDA F22 Lecture 18

Taught by

UofU Data Science

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