With the fast evolution of machine learning and the advent of generative AI, the development of recommender systems is greatly enhanced and their applications in online platforms are becoming imperative. This course introduces techniques for recommender systems and its application in a wide range of business settings such as movie recommendation, click-through-rate prediction, online dating, buyer-seller and producer-distributor matching, fashion outfit composition, and product sales forecasting. We first introduce the notion of personalization and latent representation. Then we discuss canonical recommender systems, context-aware recommender systems, deep-learning-empowered recommender systems, and recommendations with auxiliary information. Finally, we demonstrate the applications of recommender systems in several business settings, where business analysts will be equipped with recognize and disentangle complex online platform matching problems with the techniques of recommender systems.
prereq: MSBA 6131, MSBA 6421, or instructor consent
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