Linear Algebra in Data Science 2024th Edition

Linear Algebra in Data Science 2024th Edition book cover

Linear Algebra in Data Science 2024th Edition

Author(s): Peter Zizler (Author), Roberta La Haye (Author)

  • Publisher: Birkhäuser
  • Publication Date: 15 May 2024
  • Edition: 2024th
  • Language: English
  • Print length: 207 pages
  • ISBN-10: 3031549074
  • ISBN-13: 9783031549076

Book Description

This textbook explores applications of linear algebra in data science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. Linear Algebra in Data Science 2024th Edition is suitable as a supplement to a standard linear algebra course.

Editorial Reviews

Review

“Linear algebra in data science is a remarkable resource that seamlessly connects theoretical principles with practical applications. Zizler and La Haye have created an insightful and engaging guide that caters to a broad audience, from students to seasoned professionals. … this book empowers readers to apply linear algebra in diverse data science contexts. It is a must-have for anyone seeking to deepen their understanding of the mathematical frameworks driving modern data science.” (Pagadala Usha, Computing Reviews, June 4, 2025)

From the Back Cover

This textbook explores applications of linear algebra in data science at an introductory level, showing readers how the two are deeply connected. The authors accomplish this by offering exercises that escalate in complexity, many of which incorporate MATLAB. Practice projects appear as well for students to better understand the real-world applications of the material covered in a standard linear algebra course. Some topics covered include singular value decomposition, convolution, frequency filtering, and neural networks. Linear Algebra in Data Science 2024th Edition is suitable as a supplement to a standard linear algebra course.

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