闪播福利库

This course focuses on the fundamental theory, methodologies, algorithms and software tools for predictive analytics. The main goal is to equip the students with the basic knowledge and skills to solve common predictive analytics problems arising from various applications. Methodologies covered in this course include linear and non-linear regression, additive models, ensemble trees, model assessment and selection, Artificial Neural Network. Students will learn how to implement the methods using popular statistical computing and analytics tools. Working knowledge of multi-variate calculus based probability and statistical inference is expected. Prerequisite: 翱笔础狈听50003. (Typically offered: Fall, Spring and Summer)