Linear Algebra With Machine Learning And Data Av Crista (elon University North Carolina Usa) Arangala

<P>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. </P><P></P><P>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. </P><P></P><P>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. </P><P></P><P>All data sets, as well as Python and R syntax are provided to the reader through links to Gith

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