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Linear Algebra With Machine Learning and Data
Engelsk Hardback
Linear Algebra With Machine Learning and Data
Engelsk Hardback

830 kr
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6 - 8 hverdage

Om denne bog

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.

Product detaljer
Sprog:
Engelsk
Sider:
290
ISBN-13:
9780367458393
Indbinding:
Hardback
Udgave:
ISBN-10:
036745839X
Kategori:
Udg. Dato:
9 maj 2023
Længde:
23mm
Bredde:
241mm
Højde:
162mm
Forlag:
Taylor & Francis Ltd
Oplagsdato:
9 maj 2023
Forfatter(e):
Kategori sammenhænge