PCA for Data Science: Practical Dimensionality Reduction Techniques Using Python and Real-World Examples
by Paul Benson
Learn practical PCA techniques for dimensionality reduction in Python with real-world examples to simplify complex datasets.
About This Book
This book introduces principal component analysis as a core technique for reducing data dimensions while preserving essential information.
Readers learn how to implement PCA using Python and apply it to practical datasets across various domains.
The content focuses on clear explanations and step-by-step examples to support effective learning and application.
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