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Linear Algebra, Data Science, and Machine Learning

This text provides a mathematically rigorous introduction to modern methods of machine learning and data analysis at the advanced undergraduate/beginning graduate level. The book is self-contained and requires minimal mathematical prerequisites. There is a strong focus on learning how and why algori...

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Bibliographic Details
Main Authors:	Calder, Jeff (Author), Olver, Peter J. (Author)
Corporate Author:	SpringerLink (Online service)
Format:	Electronic eBook
Language:	English
Published:	Cham : Springer Nature Switzerland : Imprint: Springer, 2025.
Edition:	1st ed. 2025.
Series:	Springer Undergraduate Texts in Mathematics and Technology,
Subjects:	Algebras, Linear. Artificial intelligence > Data processing. Machine learning. Mathematical optimization. Probabilities. Linear Algebra. Data Science. Machine Learning. Optimization. Applied Probability.
Online Access:	https://doi.org/10.1007/978-3-031-93764-4
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