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Linear Algebra in Data Science / by Peter Zizler, Roberta La Haye

By: Contributor(s): Resource type: Ressourcentyp: Buch (Online)Book (Online)Language: English Series: Compact Textbooks in MathematicsPublisher: Cham : Springer International Publishing, 2024Publisher: Cham : Imprint: Birkhäuser, 2024Edition: 1st ed. 2024Description: 1 Online-Ressource(VIII, 199 p. 23 illus., 9 illus. in color.)ISBN:
  • 9783031549083
Subject(s): Additional physical formats: 9783031549076 | 9783031549090 | Erscheint auch als: 9783031549076 Druck-Ausgabe | Erscheint auch als: 9783031549090 Druck-AusgabeDDC classification:
  • 512.5 23
DOI: DOI: 10.1007/978-3-031-54908-3Online resources: Summary: 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 is suitable as a supplement to a standard linear algebra course.PPN: PPN: 1889375217Package identifier: Produktsigel: ZDB-2-SEB | ZDB-2-SMA | ZDB-2-SXMS
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