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Practical Linear Algebra for Data Science

Mike X. Cohen
4.9/5 (27018 ratings)
Read Now Download Now ⏭ listen AudioBook
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 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 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 analysisWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Practical Linear Algebra for Data Science. To get started finding Practical Linear Algebra for Data Science, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
372
Format
PDF, EPUB & Kindle Edition
Publisher
O'Reilly Media, Inc.
Release
2022
ISBN
1098120574

Practical Linear Algebra for Data Science

Mike X. Cohen
4.4/5 (1290744 ratings)
Read Now Download now ⏭ listen AudioBook
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 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 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 analysisWe have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with Practical Linear Algebra for Data Science. To get started finding Practical Linear Algebra for Data Science, you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.
Pages
372
Format
PDF, EPUB & Kindle Edition
Publisher
O'Reilly Media, Inc.
Release
2022
ISBN
1098120574

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