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Data science : an introduction to statistics and machine learning

By: Material type: TextTextPublication details: Germany: Springer Nature, 2023.Description: xxiv, 361pISBN:
  • 9783662678817
Subject(s): DDC classification:
  • 006.312 PLA PLA
Summary: This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of data science. It covers essential parts of data organization, descriptive and inferential statistics, probability theory, and machine learning. These topics are presented in a clear and mathematical sound way to help readers gain a deep and fundamental understanding. Numerous application examples based on real data are included. The book is well-suited for lecturers and students at technical universities, and offers a good introduction and overview for people who are new to the subject. Basic mathematical knowledge of calculus and linear algebra is required.
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Item type Current library Call number Status Barcode
Book Book International Management Institute New Delhi General stacks 006.312 PLA (Browse shelf(Opens below)) Available 22153

Includes bibliographical references and index.

This textbook provides an easy-to-understand introduction to the mathematical concepts and algorithms at the foundation of data science. It covers essential parts of data organization, descriptive and inferential statistics, probability theory, and machine learning. These topics are presented in a clear and mathematical sound way to help readers gain a deep and fundamental understanding. Numerous application examples based on real data are included. The book is well-suited for lecturers and students at technical universities, and offers a good introduction and overview for people who are new to the subject. Basic mathematical knowledge of calculus and linear algebra is required.

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