Machine Learning Foundations by Taeho Jo

Machine Learning Foundations by Taeho Jo

This book provides conceptual understanding of machine learning algorithms though supervised, unsupervised, and advanced learning techniques. The book consists of four parts: foundation, supervised learning, unsupervised learning, and advanced learning. The first part provides the fundamental materials, background, and simple machine learning algorithms, as the preparation for studying machine learning algorithms. The second and the third parts provide understanding of the supervised learning algorithms and the unsupervised learning algorithms as the core parts. The last part provides advanced machine learning algorithms: ensemble learning, semi-supervised learning, temporal learning, and reinforced learning.

• Provides comprehensive coverage of both learning algorithms: supervised and unsupervised learning;
• Outlines the computation paradigm for solving classification, regression, and clustering;
• Features essential techniques for building the a new generation of machine learning.

Dr. Taeho Jo works as a faculty member for school of game in Hongik University, South Korea. He received his PhD from University of Ottawa in 2006. His research spans text mining, neural networks, machine learning, and information retrieval. He has four years' experience working for industrial organizations and ten years' experience working for in academia. He has published almost 150 research papers, and he was awarded two times in the world wide biography dictionary, Marquis Who's Who in the World.