Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML
商品編號：W41961
出版日期：2024/12/20
再版日期：
商品來源：
商品主題：General Management/Strategy; Information Systems
商品類型：
涵蓋議題：Machine learning;Supervised machine learning;Unupervised machine learning;Reinforcement machine learning
難易度：4 - Undergraduate/MBA
內容長度：5 頁
地域：Canada
產業：Social Advocacy Organizations
事件年度：2024
This exercise provides a structured framework for introducing business students to supervised machine learning (SML), unsupervised machine learning (UML), and reinforcement machine learning (RML). The exercise revolves around applying these techniques to evaluate harassment policies, offering a hands-on and practical approach to understanding how machine learning (ML) works in real-world scenarios. The exercise is suitable for undergraduate classes and graduate business classes, particularly in core information technology (IT) management, innovation management, fundamentals of AI, and governance courses.
教學手冊：Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML - Teaching Note
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