Machine learning, at its core, is concerned with algorithms that transform information into actionable intelligence. As a result, machine learning is well suited to the Big Data age we’re in right now. It would be practically difficult to keep up with the tremendous influx of information without machine learning.
This book serves as a textbook for students and researchers in the subject of machine learning. It provides the theoretical framework and conceptual tools necessary for the debate and explanation of algorithms, and it covers essential current themes in machine learning. It also explains a number of important features of the algorithms’ use.
Students and researchers in machine learning, statistics, and other relevant fields may find this book useful. For graduate and advanced undergraduate courses in machine learning, or as a reference work for a research seminar, this book is an excellent resource for students.