02016 a2200229 4500
427778
427778
ISI Library, Kolkata
20200731141427.0
200623b ||||| |||| 00| 0 eng d
9789813229686
ISI Library
English
23
006.3101515
Si593
Simovici, Dan
author
Mathematical Analysis for Machine Learning and Data Mining/
Dan Simovici
World Scientific,
[2018]
Singapore:
xv, 968 pages,
23cm.
Includes bibliographical references and index
Preface --
Part I. Set-Theoretical and Algebraic Preliminaries --
Preliminaries --
Linear Spaces --
Algebra of Convex Sets --
Part II. Topology --
Topology --
Metric Space Topologies --
Topological Linear Spaces --
Part III. Measure and Integration --
Measurable Spaces and Measures --
Integration --
Part IV. Functional Analysis and Convexity --
Banach Spaces --
Differentiability of Functions Defined on Normed Spaces --
Hilbert Spaces --
Convex Functions --
Part V. Applications --
Optimization --
Iterative Algorithms --
Neural Networks --
Regression --
Support Vector Machines --
Bibliography --
Index.
This compendium provides a self-contained introduction to mathematical analysis in the field of machine learning and data mining. The mathematical analysis component of the typical mathematical curriculum for computer science students omits these very important ideas and techniques which are indispensable for approaching specialized area of machine learning centered around optimization such as support vector machines, neural networks, various types of regression, feature selection, and clustering. The book is of special interest to researchers and graduate students who will benefit from these application areas discussed in the book.
Machine Learning-Mathematics
Data Mining-Mathematics
ddc
BK
0
0
0
0
MAIN
MAIN
2020-02-21
584
12755.55
006.3101515 Si593
138443
2020-02-21
BK