Practical Linear Algebra for Data Science

Mike X Cohen

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Language: English

Published by O'Reilly Media, US, 2022

1098120612 / 9781098120610

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If you want to work in any computational or technical field, you need to understand linear algebra. As the study of matrices and operations acting upon them, linear algebra is the mathematical basis of nearly all algorithms and analyses implemented in computers. But the way it's presented in decades-old textbooks is much different from how professionals use linear algebra today to solve real-world modern applications.This practical guide from Mike X Cohen teaches the core concepts of linear algebra as implemented in Python, including how they're used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, you'll be able to understand, implement, and adapt myriad modern analysis methods and algorithms.Ideal for practitioners and students using computer technology and algorithms, this book introduces you to:The interpretations and applications of vectors and matricesMatrix arithmetic (various multiplications and transformations)Independence, rank, and inversesImportant decompositions used in applied linear algebra (including LU and QR)Eigendecomposition and singular value decompositionApplications including least-squares model fitting and principal components analysis.

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Title
Practical Linear Algebra for Data Science
Author
Mike X Cohen
Publisher
O'Reilly Media, US
Publication year
2022
Condition
New
Binding
Paperback
Language
English
ISBN 10
1098120612
ISBN 13
9781098120610

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