Name: Linear Algebra With Machine Learning and Data (Textbooks in Mathematics) (en Inglés)
SKU: 54911787
Price: 107.08 USD
Availability: InStock
Author: Crista Arangala
ISBN: 9780367458393

portada Linear Algebra With Machine Learning and Data (Textbooks in Mathematics) (en Inglés)

Linear Algebra With Machine Learning and Data (Textbooks in Mathematics) (en Inglés)

Formato

Libro Físico

Editorial

Chapman And Hall/Crc,

Autor

Crista Arangala

Idioma

Inglés

N° páginas

310

Encuadernación

Tapa Dura

ISBN13

9780367458393

N° edición

Linear Algebra With Machine Learning and Data (Textbooks in Mathematics) (en Inglés)

Crista Arangala (Autor) · Chapman And Hall/Crc, · Tapa Dura

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Reseña del libro "Linear Algebra With Machine Learning and Data (Textbooks in Mathematics) (en Inglés)"

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 and 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 are assumed; however, an overview of key concepts are presented in the Introduction and as needed throughout the text.