Machine learning models and algorithms for big data classification. Thinking with examples for effective learning
This book focuses on how to address big data classification problems using different machine learning techniques. As such it provides a readable, technical, description of the whole area of machine learning applied on big data that can be understood and enjoyed by students and researchers from many areas of computer science, statistics, biology and chemistry who are seeking to understand how these new technologies can benefit their special areas. Throughout, there are lots of examples, web-links and illustrations that make it easy for the novice to appreciate the concepts. Chapter 1 provides a general introduction to Science of Information. The book then divides into four parts. The first part deals with basic concepts of big data; the second part presents big data systems, whereas parts three and four describe different machine learning techniques. Overall, this is an excellent introduction to the main ideas for using machine learning algorithms for big data classification. As such, it provides a technical description of the topic that illustrates applicability of the subject.
scientific article; zbMATH DE number 6813234