Support Vector Machines Succinctly by Alexandre Kowalczyk
Book Contents :-
1. Prerequisites
2. The Perceptron
3. The SVM Optimization Problem
4. Solving the Optimization Problem
5. Soft Margin SVM
6. Kernels
7. The SMO Algorithm
8. Multi-Class SVMs
A. Datasets
B. The SMO Algorithm
About this book :-
"Support Vector Machines Succinctly" by Alexandre Kowalczyk is a concise and practical guide to understanding one of the most powerful "supervised learning" techniques: "support vector machines (SVMs)". The book introduces the core concepts behind SVMs in a clear, accessible way, making it ideal for students, developers, and machine learning beginners. It balances theoretical understanding with practical implementation, helping readers build confidence in applying SVMs to real-world data.
The book begins with foundational topics such as linear classification, the Perceptron, and the SVM optimization problem. It explains "soft margins", the "kernel trick" for handling non-linear data, and algorithms like Sequential Minimal Optimization (SMO). Each concept is illustrated with practical examples and code snippets, enabling readers to translate theory into actionable machine learning models. The author also discusses extensions for "multi-class classification", showing how SVMs can be applied beyond simple binary tasks.
Overall, this book equips readers with the knowledge to implement "classification models", understand optimization techniques, and use SVMs effectively in real-world applications. By combining theory, algorithms, and hands-on examples, it provides a solid foundation in SVMs and builds skills for tackling complex "machine learning" problems, making it a valuable resource for anyone entering the field of predictive modeling and data science.
Book Detail :-
Title:
Support Vector Machines Succinctly by Alexandre Kowalczyk
Publisher:
Syncfusion Inc
Year:
2017
Pages:
116
Type:
PDF
Language:
English
ISBN-10 #:
0387772413
ISBN-13 #:
978-0387772417
License:
External Educational Resource
Amazon:
Amazon
About Author :-
The author
Alexandre Kowalczyk
is a software developer and machine learning practitioner with expertise in "support vector machines" and applied AI. He works at "ABC Arbitrage", specializing in automated trading systems, and developed his skills through online courses and hands-on projects applying statistical learning to real-world datasets. His expertise spans "machine learning, SVM implementation, data classification, R and Python programming, and algorithm optimization". Kowalczyk authored "Support Vector Machines Succinctly", offering clear explanations and practical examples. He also contributes tutorials and participates in competitions, helping developers and data scientists understand and implement robust SVM models effectively in real-world applications.
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