Erscheint: Januar 2027
Buch (Softcover): Sachbuch
Linear Algebra for Data Science
Verlag:
Cambridge Academic Unsere-Artikel-Nr.: P35516648
EAN: 9781009663717
Erscheint: Januar 2027
Versand: Kostenlos
-11.9 %
CHF 109.–
CHF 96.–
Beschreibung
This accessible yet rigorous textbook introduces the fundamentals of linear algebra in the context of real-world data science applications. Including the latest developments in the field, clear and detailed mathematical explanations. and extensive examples, it offers a comprehensive and approachable introduction to the subject, focusing on the foundations of the singular value decomposition and its many uses. Key topics include matrix subspaces, reduced-rank matrix approximation, angles between subspaces, averaging subspaces, spectral embedding algorithms including Laplacian eigenmaps and multidimensional scaling, the K-SVD dictionary learning algorithm, and the generalized singular value decomposition. The text takes a practical approach, featuring real-world application examples and more than 600 end-of-chapter exercises. Accompanying online resources include a solutions manual for instructors, data sets, and MATLAB and Python code for implementing algorithms in the text.
Spezifikationen
Sprache
- Englisch
Autor
- Michael Kirby
Erscheinungsjahr
- 2027
Format
- Buch (Softcover)