000			02472nam a22002777a 4500
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020			_a9783030069490
040			_aNISER LIBRARY _beng _cNISER LIBRARY
082			_a004.852 _bMEL-M
100			_aMello, Rodrigo Fernandes de
245			_aMachine learning : _ba practical approach on the statistical learning theory
260			_aCham, Switzerland : _bSpringer, _c2018.
300			_axv, 362 pages.
504			_aIncludes bibliographical references
520			_aThis book presents the Statistical Learning Theory in a detailed and easy to understand way, by using practical examples, algorithms and source codes. It can be used as a textbook in graduation or undergraduation courses, for self-learners, or as reference with respect to the main theoretical concepts of Machine Learning. Fundamental concepts of Linear Algebra and Optimization applied to Machine Learning are provided, as well as source codes in R, making the book as self-contained as possible. It starts with an introduction to Machine Learning concepts and algorithms such as the Perceptron, Multilayer Perceptron and the Distance-Weighted Nearest Neighbors with examples, in order to provide the necessary foundation so the reader is able to understand the Bias-Variance Dilemma, which is the central point of the Statistical Learning Theory. Afterwards, we introduce all assumptions and formalize the Statistical Learning Theory, allowing the practical study of different classification algorithms. Then, we proceed with concentration inequalities until arriving to the Generalization and the Large-Margin bounds, providing the main motivations for the Support Vector Machines. From that, we introduce all necessary optimization concepts related to the implementation of Support Vector Machines. To provide a next stage of development, the book finishes with a discussion on SVM kernels as a way and motivation to study data spaces and improve classification results.
650			_aMachine learning
650			_aStatistical learning theory
650			_aData science
650			_aSupport vector machines
700			_aPonti, Maocir Antonelli
856			_3Table of content _uhttps://link.springer.com/content/pdf/bfm:978-3-319-94989-5/1
856			_3Reviews _uhttps://www.goodreads.com/book/show/41131600-machine-learning?ref=nav_sb_ss_1_13#CommunityReviews
942			_2udc _cBK
999			_c35889 _d35889