Business Analytics Roll 25421 Prajkta Jawanjal
Across
- 2. Comparing two versions to find a winner
- 4. Considerations around responsible data use
- 5. Variance tradeoff / systematic error in models
- 8. Algorithms that learn patterns from data
- 10. Measure of likelihood of events
- 11. Layered model inspired by biological neurons
- 12. Controlled tests to compare alternatives
- 13. Formal statement tested with data
- 15. Grouping similar observations without labels
- 18. Curse when features outnumber samples
- 19. Fundamental branch for describing and summarizing data
- 21. Applying statistical methods to economics
- 28. Tools and practices for reporting
- 31. Learning without labeled outputs
- 32. Forecasting future values from past data
- 33. Assigning items to predefined categories
- 34. Analysis of data indexed in time order
- 35. Ensemble of decision tree models
- 36. Assessing model performance on new data
- 38. Technique for predicting a continuous outcome
Down
- 1. Graphical representation of data insights
- 3. Centralized repository for integrated data
- 6. Extremely large datasets needing special tools
- 7. Determining positive or negative opinion in text
- 9. On-demand compute and storage services
- 14. Process of finding best possible solution
- 16. Structured query language for databases
- 17. General-purpose language used for data analysis
- 19. Learning with labeled training data
- 20. Principal component analysis for dimensionality_reduction
- 22. Programming language popular for statistics
- 23. Extracting insights from unstructured text
- 24. Discovering patterns in large datasets
- 25. Extract, transform and load (data pipeline step)
- 26. Neural-network-based machine learning approach
- 27. Statistical approach using prior beliefs
- 29. Real-time processing of continuous data flows
- 30. Tree-shaped predictive model
- 37. Visual displays of key performance metrics