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Let the machines do what they do best. The 37th installment of the Crash Course Statistics series focuses on unsupervised machine learning. It describes two methods, k-means and hierarchical clustering, and provides examples for each.
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Instructional Ideas
- Have the class create graphic organizers comparing supervised and unsupervised machine learning
Classroom Considerations
- Learners should be familiar with machine learning from the previous video
- Note that one of the examples focuses on autism spectrum disorders
- This video is hosted on YouTube
Pros
- Easy for teenagers to relate to the examples
- Graphics help hold viewer interest
Cons
- None