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Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization Paperback - 2023

by B.K. Tripathy

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Paperback. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; This book describes algorithms like Locally Linear Embedding, Laplacian eigenmaps, Semidefinite Embedding, t-SNE to resolve the problem of dimensionality reduction in case of non-linear relationships within the data. Underlying mathemat
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Details

  • Title Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization
  • Author B.K. Tripathy
  • Binding Paperback
  • Condition New
  • Pages 160
  • Volumes 1
  • Language ENG
  • Publisher CRC Press
  • Publication date 2023-09-25
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # ria9781032041032_inp
  • ISBN 9781032041032 / 103204103X
  • Weight 0.56 lbs (0.25 kg)
  • Dimensions 9.21 x 6.14 x 0.38 in (23.39 x 15.60 x 0.97 cm)
  • Category Business / Economics / Finance
  • Library of Congress subjects Machine learning, Information visualization
  • Library of Congress Catalogue Number 2021012896
  • Dewey Decimal Code 001.422
  • Quantity available 84

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Reader reviews for Unsupervised Learning Approaches for Dimensionality Reduction and Data Visualization

From the publisher

This book describes algorithms like Locally Linear Embedding, Laplacian eigenmaps, Semidefinite Embedding, t-SNE to resolve the problem of dimensionality reduction in case of non-linear relationships within the data. Underlying mathematical concepts, derivations, proofs, strengths and limitations of these algorithms are discussed as well.

About the author

B.K. Tripathy, Anveshrithaa Sundareswaran, Shrusti Ghela
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