Chapter 2: Introduction to Dimensionality Reduction

This chapter introduces the basics of Introduction to Dimensionality Reduction. You will learn essential concepts and techniques.

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Chapter Contents

What is Dimensionality Reduction - Visualization and compression of high-dimensional data
Principal Component Analysis (PCA) - Linear transformation that maximizes variance
t-SNE - Nonlinear dimensionality reduction and visualization
UMAP - Fast and flexible dimensionality reduction
Application Examples - Visualization of image data and text data

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