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How would you approach building an unsupervised learning model to detect outliers in a dataset with 6 behavioral variables and 25 contextual attributes, which needs normalization? Additionally, what evaluation metrics and visualizations would you use to measure the performance of the model?
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Data Analyst
Marketer
General
Structure your answer around preprocessing (normalization strategies), model selection (isolation forest, LOF, etc.), and evaluation techniques that address the challenge of not having ground truth labels.
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Very hard Difficulty
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ML Case question
ML Case questions present machine learning scenarios to assess your applied AI knowledge. Demonstrate your approach to framing problems, selecting appropriate models, evaluating performance, and deploying machine learning solutions effectively.