Class 12 02

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Across
  1. 5. Making the trained model available to users
  2. 7. Process of gathering observations and measurements
  3. 10. Stage where data is cleaned and transformed
  4. 13. First step of Data Science Methodology where the problem is defined
  5. 15. Type of analytics that predicts future outcomes
  6. 16. Metric that measures proportion of predicted positives that are correct
Down
  1. 1. Understanding whether collected data represents the problem
  2. 2. Measure used to evaluate classification performance using TP, TN, FP, FN
  3. 3. Technique that divides data into multiple folds
  4. 4. Final stage of Data Science Methodology
  5. 6. Technique that divides data into training and testing sets
  6. 8. Process of creating new useful features from existing data
  7. 9. Popular programming language used in Data Science
  8. 11. Metric that measures correctly classified positives
  9. 12. Error metric commonly used in regression models
  10. 14. Stage where AI models are developed