Lesson 1,
Topic 1
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Supervised and Unsupervised Models
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Question: Can you describe the difference between supervised and unsupervised learning?
- These are machine learning classifications.
- Study the definitions ahead of time and focus on algorithms you know.
Example: The difference between supervised and unsupervised learning is in what type of data you’re analyzing, and how. Supervised data is labeled and the goal is usually prediction– for instance, classification and regression type algorithms. Unsupervised learning uses unlabeled input data, best for analysis. They help with classification too, but also density estimation and dimension reduction.