Practical Linear Algebra for Data Science: From Core Concepts to Applications Using Python
by Mike X Cohen
Practical Linear Algebra for Data Science presents the essential ideas of linear algebra through a data science lens. With applications using Python, Mike X Cohen connects foundational mathematics to practical computation, offering readers a focused way to develop skills relevant to analysis, modeling, and other data-oriented work.
About This Book
Practical Linear Algebra for Data Science introduces linear algebra in the context of modern data science.
The book connects core mathematical concepts with applications using Python, helping readers relate theory to computation.
Its practical focus makes it a resource for studying how linear algebra supports data-oriented work.
Written by Mike X Cohen, this guide is designed for readers seeking an accessible bridge between mathematical foundations and Python-based applications.
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