Machine learning for text

By:

Aggarwal, Charu C

Material type: Text

TextPublication details: Switzerland: Springer Nature, 2023.Edition: 2nd edDescription: xxiii, 565 pISBN:

9783030966225

Subject(s):

DDC classification:

006.312 AGG AGG

Summary: This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.

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Holdings
Item type	Current library	Call number	Status	Barcode
Book	International Management Institute New Delhi General stacks	006.312 AGG (Browse shelf(Opens below))	Available	22151

Includes bibliographical references and index.

This second edition textbook covers a coherently organized framework for text analytics, which integrates material drawn from the intersecting topics of information retrieval, machine learning, and natural language processing. Particular importance is placed on deep learning methods. The chapters of this book span three broad categories:1. Basic algorithms: Chapters 1 through 7 discuss the classical algorithms for text analytics such as preprocessing, similarity computation, topic modeling, matrix factorization, clustering, classification, regression, and ensemble analysis.

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