HADM 4750: Machine Learning for Business and Hospitality Applications
Spring. 1.5 credits. Student option grading.
Prerequisite: HADM 2010 or HADM 2011 or HADM 2021 or HADM 3010. Priority given to: SHA students. Course can qualify for Hospitality Analytics Specialization elective. Co-meets with HADM 6750.
Limited to HotelDM 4750 Pre-Req
- Meng Qi (mq56) - Spring 2024
The world is becoming increasingly data driven. In this context, the ability to leverage machine learning techniques to extract value from data is vital across many businesses, including the hospitality industry. This course is designed to meet the emerging need of this sector. This course aims to convey core principles of machine learning and hands-on applications of on solving real business problems. This course emphasizes on how to draw managerial insights and support business decisions from data. The methods that would be covered include linear regression, logistic regression, classification trees, clustering, and neural networks. This course also explains concepts including bias-variance trade-off, model interpretability, cross-validation, prescriptive analytics, and ethical concerns of machine learning.