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Mathematical Foundations for Data Analysis

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Provides accessible, simplified introduction to core mathematical language and concepts Integrates examples of key concepts through geometric illustrations and Python coding Addresses topics in locality sensitive hashing, graph-structured data, and big data processing as well as basic linear algebra Includes perspectives on ethics in data

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Provides accessible, simplified introduction to core mathematical language and concepts Integrates examples of key concepts through geometric illustrations and Python coding Addresses topics in locality sensitive hashing, graph-structured data, and big data processing as well as basic linear algebra Includes perspectives on ethics in data

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Book Format

Hardcover, Softcover

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Book information

Edition
1st Edition
ISBN [Hardcover]
9783030623401
ISBN [Softcover]
9783030623432
Publisher
Springer
Year
2021
Pages
XVII, 287 p.
Series Title
Springer Series in the Data Sciences
Language
English
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