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5 cards from this section. Quick, good the night before a test.
What is data exploration?
Consider why we examine data before modeling.
Why is detecting outliers important?
Think about how they could influence predictions.
Why is it important to detect outliers in data exploration?
Think about how they affect averages.
Is analyzing feature relationships essential in data exploration?
Think about what features you'd include in your model.
Given a dataset showing daily temperatures, identify any outliers. What implications could they have on your understanding of climate patterns?
Look for unusually high or low numbers compared to average temperatures.
You have a dataset with client purchase history. How would you determine the relationships between product categories? Elaborate on potential methods.
Think about how changes in one category might affect another.
5 more questions in this section. Enroll free to practise them all.
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