An overview of core machine learning technologies with motivating applications from a variety of disciplines and real‐world data sets. Students will learn how to implement, evaluate, and improve machine learning algorithms. While studying best practice in machine learning, students are introduced to data mining and statistical pattern recognition and learn how to build automatic analytical models. Topics include identification and extraction of useful features that best represent available data, some of the most important machine learning algorithms, and the evaluation of algorithm performance.