Book Description
Support Vector Machines (SVMs) are some of the most performant off-the-shelf, supervised machine-learning algorithms. In Support Vector Machines Succinctly, author Alexandre Kowalczyk guides readers through the building blocks of SVMs, from basic concepts to crucial problem-solving algorithms. He also includes numerous code examples and a lengthy bibliography for further study. By the end of the book, SVMs should be an important tool in the reader's machine-learning toolbox.
This open book is licensed strictly for personal or educational use. You can download Support Vector Machines Succinctly ebook for free in PDF format (3.7 MB).
Table of Contents
Chapter 1
Prerequisites
Chapter 2
The Perceptron
Chapter 3
The SVM Optimization Problem
Chapter 4
Solving the Optimization Problem
Chapter 5
Soft Margin SVM
Chapter 6
Kernels
Chapter 7
The SMO Algorithm
Chapter 8
Multi-Class SVMs
Chapter 9
Conclusion
Appendix A
Datasets
Appendix B
The SMO Algorithm
Book Details
Title
Support Vector Machines Succinctly
Subject
Computer Science
Publisher
Syncfusion
Published
2017
Pages
114
Edition
1
Language
English
PDF Size
3.7 MB
License
For personal or educational use
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