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Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML
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. -
Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML - SH Policy 1
Supplemental material to accompany product W41961. -
Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML - SH Policy 2
Supplemental material to accompany product W41961. -
Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML - SH Policy 3
Supplemental material to accompany product W41961. -
Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML - SML Rubric
Supplemental material to accompany product W41961. -
Learning Machine Learning: A Hands-On Comparison of SML, UML, AND RML - SML Rubric Labelled
Supplemental material to accompany product W41961.