Machine Learning: A Practical Approach on the Statistical Learning Theory

Author:   RODRIGO F MELLO ,  Moacir Antonelli Ponti
Publisher:   Springer Nature Switzerland AG
Edition:   Softcover reprint of the original 1st ed. 2018
ISBN:  

9783030069490


Pages:   362
Publication Date:   01 February 2019
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
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Machine Learning: A Practical Approach on the Statistical Learning Theory


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Author:   RODRIGO F MELLO ,  Moacir Antonelli Ponti
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   Softcover reprint of the original 1st ed. 2018
Dimensions:   Width: 15.50cm , Height: 2.00cm , Length: 23.50cm
Weight:   0.581kg
ISBN:  

9783030069490


ISBN 10:   3030069494
Pages:   362
Publication Date:   01 February 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

Chapter 1 – A Brief Review on Machine Learning.- Chapter 2 - Statistical Learning Theory.- Chapter 3 - Assessing Learning Algorithms.- Chapter 4 - Introduction to Support Vector Machines.- Chapter 5 - In Search for the Optimization Algorithm.- Chapter 6 - A Brief Introduction on Kernels.- 

Reviews

The book addresses the subject of machine learning, with an emphasis on statistical learning theory. ... The book can be used in ML courses as well as for independent study, since it presents very thoroughly all the fundamental theoretical insights of SLT, together with examples and implementations in R. (Catalin Stoean, zbMATH 1408.68003, 2019)


“The book addresses the subject of machine learning, with an emphasis on statistical learning theory. … The book can be used in ML courses as well as for independent study, since it presents very thoroughly all the fundamental theoretical insights of SLT, together with examples and implementations in R.” (Catalin Stoean, zbMATH 1408.68003, 2019)


Author Information

riggerRodrigo Fernandes de Mello is Associate Professor with the Department of Computer Science, at the Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, SP, Brazil. He obtained his PhD degree from the University of São Paulo. His research interests include the Statistical Learning Theory, Machine Learning, Data Streams, and Applications in Dynamical Systems concepts. He has published more than 100 papers including journals and conferences, supported and organized international conferences, besides serving as Editor of International Journals. Moacir Antonelli Ponti is Associate Professor with the Department of Computer Science, at the Institute of Mathematics and Computer Sciences, University of São Paulo, São Carlos, Brazil, and was visiting researcher at the Centre for Vision, Speech and Signal Processing (CVSSP), University of Surrey. He obtained his PhD from the Federal University of São Carlos. His research interests include Pattern Recognition and Computer Vision, as well as Signal, Image and Video Processing.

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