Description
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 its 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 theyre used in data science, machine learning, deep learning, computational simulations, and biomedical data processing applications. Armed with knowledge from this book, youll 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
Author: Mike Cohen
Binding Type: Paperback
Publisher: OReilly Media
Published: 10/11/2022
Pages: 326
Weight: 1.5lbs
Size: 9.10h x 6.90w x 0.70d
ISBN: 9781098120610
Language: English
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