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Learn about the fundamental distinctions between discriminative and generative models in machine learning through a concise 13-minute lecture that explores their core differences. Examine how generative models differ from the discriminative approaches covered throughout the semester, delve into the generative story behind naïve Bayes, and understand when to apply each modeling approach in practical machine learning applications.
Syllabus
What we saw most of the semester
Generative models
Example: Generative story of naïve Bayes
Generative vs Discriminative models
Taught by
UofU Data Science