Support Vector Machines Succinctly

Support Vector Machines Succinctly

OVERVIEW
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.

TABLE OF CONTENTS
Prerequisites

The Perceptron

The SVM Optimization Problem

Solving the Optimization Problem

Soft Margin SVM

Kernels

The SMO Algorithm

Multi-Class SVMs

Conclusion

Appendix A: Datasets

Appendix B: The SMO Algorithm

Author
Alexandre Kowalczyk
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http://up-4ever.org/d/B484