Simovici, Dan A. <br/><br/>
Mathematical analysis for machine learning and data mining / 
Dan Simovici, University of Massachusetts, Boston, USA. 
 - xv, 968 páginas 
<br/><br/>Part I.- Set-theoretical and algebraic preliminaries.<br/>1.- Preliminaries -- 2.- Linear spaces -- 3.- Algebra of convex sets.<br/>Part II.- Topology.<br/>4.- Topology -- 5.- Metric space topologies -- 6.- Topological linear spaces.<br/>Part III.- Measure and integration.<br/>7.- Measurable spaces and measures -- 8.- Integration.<br/>Part IV.- Functional analysis and convexity.<br/>9.- Banach spaces -- 10.- Differentiability of functions defined on normed spaces -- 11.- Hilbert spaces.<br/>Part V.- Applications.<br/>13.- Optimization -- 14.- Iterative algorithms -- 15.- Neural networks -- 16.- Regression -- 17.- Support vector mechines.- 
<br/><br/><label>ISBN: </label>9789813229686 (hc : alk. paper) 
<br/><br/><label>Subjects--Topical Terms: </label><br/>INTELIGENCIA ARTIFICIAL--MATEMATICAS<br/>BASES DE DATOS EN MINERIA--MATEMATICAS
<br/><br/><label>Dewey Class. No.: </label>006.3  / S611