Search Results
ISQA 8720 APPLIED STATISTICAL MACHINE LEARNING (3 credits)
This course focuses on advanced techniques in the analysis and evaluation of data, using both supervised and unsupervised methods. It covers the main types of statistical learning models needed for complex data analytics problems, as well as aspects of model development and optimization. Topics include: Linear and Non-Linear Regression Models, Classification, Resampling Methods, Model Selection and Regularization, Decision Trees, Model Boosting and Bagging, Support Vector Machines, and Clustering methods. This is an applied, hands-on course that will use a state-of-the-art statistical tool to implement the discussed approaches in assignments and a course project and focuses on the understanding and application of the concepts.
Prerequisite(s): ISQA 8156 (B- grade or better) and the following topics: The equivalent of two classes of statistics and/or advanced mathematics and a minimum of one semester of applying R in courses and/or projects
Business Administration, MBA and Management Information Systems, MS (MBA/MIS)
Department of Information Systems & Quantitative Analysis, College of Information Science & Technology
Business Administration, MBA
...BSAD 8210 ) 3 BSAD 8720 (prereq: completion of...such as ECON 8300 , ISQA 9130 or STAT...