Introduction to Predictive Modeling

Catalog description

This introductory course focuses on how to use predictive models to analyze data. Data in the real world involves elements of systematic patterns as well as uncertainty. The uncertainty may arise from missing information, measurement error or incomplete sampling of the population. Statistical modeling methodologies provide a set of tools for understanding data by incorporating assumptions and prior knowledge. These models are useful for supporting decision-making in many areas of computer science, including machine learning, data mining, natural language processing, computer vision, and image analysis.