INTRODUCTION TO MACHINE LEARNING

Catalog description

Combining data, computation, and inferential thinking, data science redefines how people and organizations solve challenging problems and understand their world. We explore key areas of data science, including question formulation, data collection and cleaning, visualization, statistical inference, predictive modeling, and decision-making. These include languages for transforming, querying, and analyzing data; algorithms for machine learning methods, including regression, classification, and clustering; statistical concepts of measurement error and prediction; and salable data processing techniques.