Practical Linear Algebra for Data Science is popular PDF and ePub book, written by MIKE. COHEN in 2022-11-30, it is a fantastic choice for those who relish reading online the Computers genre. Let's immerse ourselves in this engaging Computers book by exploring the summary and details provided below. Remember, Practical Linear Algebra for Data Science can be Read Online from any device for your convenience.
Practical Linear Algebra for Data Science Book PDF Summary
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
Detail Book of Practical Linear Algebra for Data Science PDF
- Author : MIKE. COHEN
- Release : 30 November 2022
- Publisher : O'Reilly Media
- ISBN : 1098120612
- Genre : Computers
- Total Page : 300 pages
- Language : English
- PDF File Size : 17,5 Mb
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