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3 cards from this section. Quick, good the night before a test.
What is supervised learning?
Think of how we learn from guides.
Define overfitting.
Consider if you memorize answers for a test but don’t understand the concepts.
What is the main purpose of model evaluation?
Think about why we check our answers after a test.
True or False: Unsupervised learning requires labeled data.
Consider the nature of the data used.
Propose a full design methodology for an AI application aimed to improve customer service in a retail setting. Outline the problem definition, algorithm selection, data sourcing, and evaluation metrics.
Think critically about each step involved and how they connect.
Analyze how improper data preprocessing might lead to model failure or inaccuracies. Provide a scenario where this could happen.
Use examples from previous discussions to illustrate your points.
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