Pattern Recognition: Fundamentals and Applications

What Is Pattern Recognition

The process of automatically recognizing patterns and regularities within data is known as pattern recognition. Statistical data analysis, signal processing, image analysis, information retrieval, bioinformatics, data compression, computer graphics, and machine learning are just few of the fields that can benefit from its use. The fields of statistics and engineering are where pattern recognition got its start; some contemporary methods of pattern recognition involve the use of machine learning, which is made possible by the increased availability of huge data and the more abundant computing capacity. Both of these pursuits might be considered to be two facets of the same application sector, and both of these activities have undergone significant development over the course of the last several decades.

How You Will Benefit

(I) Insights, and validations about the following topics:

Chapter 1: Pattern recognition

Chapter 2: Supervised learning

Chapter 3: Linear classifier

Chapter 4: Perceptron

Chapter 5: Gaussian process

Chapter 6: Expectation-maximization algorithm

Chapter 7: Generalized linear model

Chapter 8: Statistical learning theory

Chapter 9: Kernel method

Chapter 10: Probabilistic classification

(II) Answering the public top questions about pattern recognition.

(III) Real world examples for the usage of pattern recognition in many fields.

Who This Book Is For

Professionals, undergraduate and graduate students, enthusiasts, hobbyists, and those who want to go beyond basic knowledge or information for any kind of pattern recognition.

What is Artificial Intelligence Series

The artificial intelligence book series provides comprehensive coverage in over 200 topics. Each ebook covers a specific Artificial Intelligence topic in depth, written by experts in the field. The series aims to give readers a thorough understanding of the concepts, techniques, history and applications of artificial intelligence. Topics covered include machine learning, deep learning, neural networks, computer vision, natural language processing, robotics, ethics and more. The ebooks are written for professionals, students, and anyone interested in learning about the latest developments in this rapidly advancing field.
The artificial intelligence book series provides an in-depth yet accessible exploration, from the fundamental concepts to the state-of-the-art research. With over 200 volumes, readers gain a thorough grounding in all aspects of Artificial Intelligence. The ebooks are designed to build knowledge systematically, with later volumes building on the foundations laid by earlier ones. This comprehensive series is an indispensable resource for anyone seeking to develop expertise in artificial intelligence.