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Practical Linear Algebra for Data Science: From Core Concepts to Applications Using Python

Practical Linear Algebra for Data Science: From Core Concepts to Applications Using Python

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Practical Linear Algebra for Data Science: From Core Concepts to Applications Using Python

Practical Linear Algebra for Data Science: From Core Concepts to Applications Using Python

Category

Python

Data Science

Linear Algebra

Author

Mike X. Cohen

Publication

OReilly Media

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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 matrices
Matrix arithmetic (various multiplications and transformations)
Independence, rank, and inverses
Important decompositions used in applied linear algebra (including LU and QR)
Eigendecomposition and singular value decomposition
Applications including least-squares model fitting and principal components analysis

'

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ISBN-10

1098120612

ISBN-13

978-1098120610

Publisher

OReilly Media

Price

53.99

File Type

PDF

Page No.

326

Mike X. Cohen

Mike X Cohen likes to do neuroscience research, write texbooks, create online courses, and look at a ...

About the Author

Mike is an associate professor of neuroscience at the Donders Institute (Radboud University Medical Centre) in the Netherlands. He has over 20 years experience teaching scientific coding, data analysis, statistics, and related topics, and has authored several online courses and textbooks. He has a suspiciously dry sense of humor and enjoys anything purple.

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