Linear Algebra With Machine Learning and Data Hardback
by Crista (Elon University, North Carolina, USA) Arangala
Part of the Textbooks in Mathematics series
Hardback
- Information
Description
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.
Information
-
In Stock - low on stock, only 1 copy remainingFree UK DeliveryEstimated delivery 2-3 working days
- Format:Hardback
- Pages:290 pages, 130 Line drawings, black and white; 130 Illustrations, black and white
- Publisher:Taylor & Francis Ltd
- Publication Date:09/05/2023
- Category:
- ISBN:9780367458393
Information
-
In Stock - low on stock, only 1 copy remainingFree UK DeliveryEstimated delivery 2-3 working days
- Format:Hardback
- Pages:290 pages, 130 Line drawings, black and white; 130 Illustrations, black and white
- Publisher:Taylor & Francis Ltd
- Publication Date:09/05/2023
- Category:
- ISBN:9780367458393