Bøger af Darrin Thomas

Machine learning has become one of the hottest and fastest growing disciplines of the 21st century. This has resulted in a huge demand for understanding and the use of machine learning ideas and algorithms. In this text, Darrin Thomas provides explanation and examples of the implementation of machine learning algorithms using R. Various concepts such as, classification, numeric prediction, model evaluation, and model performance are discussed.

Introduction to statistics with an application of R

Machine learning has grown tremendously over the years and many of the concepts of machine learning and data science are readily available to the typical data analyst. In this text, Darrin Thomas provides explanation and examples of the implementation of machine learning algorithms using R. Various concepts such as feature selection, classification, and numeric prediction are discussed.

This book is focused primarily on unsupervised learning algorithms with a brief look at supervised learning algorithms as well. The first seven chapters focus on unsupervised learning algorithms focusing on such topics as clustering, components, and association rules. The last chapter looks at supervised learning with an explanation of K Nearest Neighbor.