Description: Practical Linear Algebra for Data Science : From Core Concepts to Applications Using Python, Paperback by Cohen, Mike X., ISBN 1098120612, ISBN-13 9781098120610, Like New Used, Free shipping in the US 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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Book Title: Practical Linear Algebra for Data Science : From Core Concepts to
Number of Pages: 326 Pages
Language: English
Publication Name: Practical Linear Algebra for Data Science : from Core concepts to Applications Using Python
Publisher: O'reilly Media, Incorporated
Subject: Algebra / Linear, Data Processing
Item Height: 0.8 in
Publication Year: 2022
Item Weight: 19.7 Oz
Type: Textbook
Subject Area: Mathematics, Computers
Author: Mike Cohen
Item Length: 9.2 in
Item Width: 7.6 in
Format: Trade Paperback
