TY  - BOOK
AU  - Arangala,Crista
TI  - Linear algebra with machine learning and data
T2  - Textbooks in mathematics
SN  - 9780367458393
U1  - 512.64:004.85 
PY  - 2023///
CY  - Boca Raton
PB  - CRC Press
KW  - Algebras, Linear
KW  - Textbooks
KW  - Machine learning
KW  - Mathematics
KW  - Data mining
N1  - Includes bibliographical references and index
N2  - This book takes a deep dive into several key linear algebra subjects as they apply to data analytics and data mining. The book offers a case study approach where each case will be grounded in a real-world application.

This text is meant to be used for a second course in applications of Linear Algebra to Data Analytics, with a supplemental chapter on Decision Trees and their applications in regression analysis. The text can be considered in two different but overlapping general data analytics categories: clustering and interpolation.

Knowledge of mathematical techniques related to data analytics and exposure to interpretation of results within a data analytics context are particularly valuable for students studying undergraduate mathematics. Each chapter of this text takes the reader through several relevant case studies using real-world data.

All data sets, as well as Python and R syntax, are provided to the reader through links to Github documentation. Following each chapter is a short exercise set in which students are encouraged to use technology to apply their expanding knowledge of linear algebra as it is applied to data analytics.

A basic knowledge of the concepts in a first Linear Algebra course is assumed; however, an overview of key concepts is presented in the Introduction and as needed throughout the text
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UR  - https://www.goodreads.com/book/show/62872757-linear-algebra-with-machine-learning-and-data?ref=nav_sb_ss_1_13#CommunityReviews
ER  -