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3 cards from this section. Quick, good the night before a test.
Define data reduction.
Think about why reducing data size could be useful.
What is sampling?
Consider how one can represent a larger group with fewer items.
What does data reduction aim to achieve?
Think about data processing and its efficiency.
True or False: Dimensionality reduction can help prevent overfitting in AI models.
Remember why we simplify datasets.
You have a dataset of 10,000 customer reviews. How would you apply sampling to gain insights while minimizing data size?
Consider methods like stratified sampling for more accuracy.
Explain a situation where choosing between sampling and dimensionality reduction is necessary. What factors would you consider?
Focus on the type of data and the desired outcome.
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