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Rapid Recall 21–40

  1. Batch layer purpose?
  2. Speed layer purpose?
  3. Serving layer purpose?
  4. What is the main trade-off in the batch/speed/serving pattern?
  5. Define supervised learning.
  6. Define unsupervised learning.
  7. Define reinforcement learning.
  8. What clue most quickly separates supervised from unsupervised?
  9. What does data profiling do?
  10. What does data reduction do?
  11. Association vs clustering?
  12. What is a self-organizing map used for at a high level?
  13. What is sentiment analysis trying to infer?
  14. Why are simple keyword counts weak for sentiment?
  15. Data mining vs predictive analytics?
  16. Predictive vs operational analytics?
  17. Name major source-selection criteria.
  18. Why does granularity matter when choosing/aligning sources?
  19. Why does update frequency/timeliness matter?
  20. Why can filtering sources introduce bias?

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