Overview and Importance of Data Quality

Overview and Importance of Data Quality

Association for Computing Machinery (ACM) via YouTube Direct link

Affecting Factor: Overlap

19 of 25

19 of 25

Affecting Factor: Overlap

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Overview and Importance of Data Quality

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  1. 1 Overview and Importance of Data Quality for Machine Learning Tasks
  2. 2 Acknowledgements
  3. 3 Data Preparation in Machine Learning
  4. 4 Challenges with Data Preparation
  5. 5 Data Quality Analysis can help..
  6. 6 Different personas in enterprise setting..
  7. 7 To put it all together
  8. 8 To summarize
  9. 9 Data Quality Metrics
  10. 10 Common Data Cleaning Techniques
  11. 11 Is data cleaning always helpful for ML pipeline?
  12. 12 Insights: Impact of different cleaning techniques
  13. 13 In conclusion
  14. 14 Why it happens?
  15. 15 Why Imbalanced Classification is Hard?
  16. 16 Evaluation Metrics for Imbalanced Datasets Accuracy Paradox
  17. 17 Factors affecting class imbalance
  18. 18 Affecting Factor: Imbalance Ratio
  19. 19 Affecting Factor: Overlap
  20. 20 Affecting Factor: Smaller sub-concepts
  21. 21 Affecting Factor: Dataset Size
  22. 22 Affecting Factor: Combined Effect
  23. 23 Modelling Strategies: Types
  24. 24 Resampling Techniques
  25. 25 Bayes Impact index

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