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 Online-Ressource
Verfasst von:Arangala, Crista [VerfasserIn]   i
Titel:Linear Algebra with machine learning and data
Verf.angabe:Crista Arangala
Ausgabe:First edition
Verlagsort:Boca Raton ; London ; New York
Verlag:CRC Press, Taylor & Francis Group
Jahr:2023
Umfang:1 Online-Ressource (xix, 289 Seiten)
Illustrationen:Illustrationen
Gesamttitel/Reihe:Textbooks in mathematics
Fussnoten:Includes bibliographical references (page 283-286) and index
ISBN:978-1-003-02567-2
Abstract:This textbook attempts to revolutionize the Advanced Linear Algebra course by offering the integration of data analysis through case studies. Many schools are trying to find ways to incorporate data analysis into the undergrad math curriculum. The author presents a real alternative to standard textbooks. The use of case studies to demonstrate how linear algebra can be used in data analysis separates this text from all others currently available from any major publisher
 1 Graph Theory. 2. Stochastic Processes. 3. SVD and PCA. 4. Interpolation. 5. Optimization and Learning Techniques for Regression. 6. Decision Trees and Random Forests. 7. Random Matrices and Covariance Estimate. 8. Sample Solutions to Exercises.
DOI:doi:10.1201/9781003025672
URL:Resolving-System: https://doi.org/10.1201/9781003025672
 Verlag: https://www.taylorfrancis.com/books/9781003025672
 DOI: https://doi.org/10.1201/9781003025672
Schlagwörter:(s)Lineare Algebra   i / (s)Maschinelles Lernen   i
Datenträger:Online-Ressource
Sprache:eng
Bibliogr. Hinweis:Erscheint auch als : Druck-Ausgabe: Arangala, Crista: Linear algebra with machine learning and data. - First edition. - Boca Raton : CRC Press, 2023. - xix, 289 Seiten
RVK-Notation:SK 220   i
 ST 300   i
Sach-SW:Algebra
 Algebra
 Angewandte Mathematik
 Applied mathematics
 Environmental science, engineering & technology
 MATHEMATICS / Algebra / General
 MATHEMATICS / General
 Umweltwissenschaften, Umwelttechnik
 MATHEMATICS / Algebra / Linear
 MATHEMATICS / Applied
K10plus-PPN:1847528791
 
 
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