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Machine Learning : A Practical Approach on the Statistical Learning Theory by Moacir Antonelli Ponti and Rodrigo Fernandes de Mello (2019, Trade Paperback)

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Product Information

This 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.

Product Identifiers

Publisher
Springer International Publishing A&G
ISBN-10
3030069494
ISBN-13
9783030069490
eBay Product ID (ePID)
20038419003

Product Key Features

Author
Rodrigo Fernandes De Mello, Moacir Antonelli Ponti
Publication Name
Machine Learning : a Practical Approach on the Statistical Learning Theory
Format
Trade Paperback
Language
English
Publication Year
2019
Type
Textbook
Number of Pages
Xv, 362 Pages

Dimensions

Item Length
9.2in
Item Height
0.8in
Item Width
6.1in
Item Weight
20.5 Oz

Additional Product Features

Number of Volumes
1 Vol.
Lc Classification Number
Q334-342
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)
Table of Content
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.-
Copyright Date
2018
Topic
Probability & Statistics / General, Computer Science, Intelligence (Ai) & Semantics
Intended Audience
Trade
Illustrated
Yes
Genre
Computers, Mathematics

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item 1 Machine Learning: A Practical Approach on the Statistical Learning Theory (Paper
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Picture 1 of 1

Machine Learning : A Practical Approach on the Statistical Learning Theory by Moacir Antonelli Ponti and Rodrigo Fernandes de Mello (2019, Trade Paperback)

About this product

Product Information

Product Identifiers

Product Key Features

Dimensions

Additional Product Features

All listings for this product

item 1 Machine Learning: A Practical Approach on the Statistical Learning Theory (Paper

item 2 Machine Learning: A Practical Approach on the Statistical Learning Theory by Moa

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