Predictive Analytics for Practitioners

Predictive Analytics for Practitioners

PASS Data Community Summit via YouTube Direct link

Data Preparation (Conditioning) Steps

8 of 19

8 of 19

Data Preparation (Conditioning) Steps

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Classroom Contents

Predictive Analytics for Practitioners

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  1. 1 Intro
  2. 2 Technical Assistance
  3. 3 What do Predictive Modelers do? The CRISP-DM Process Model
  4. 4 CRISP-DM: Business Understanding Steps
  5. 5 Objective's
  6. 6 Data Understanding Steps
  7. 7 Source Data
  8. 8 Data Preparation (Conditioning) Steps
  9. 9 Data Size
  10. 10 Modeling Steps
  11. 11 Sampling
  12. 12 Classifiers Find Different Decision Boundaries
  13. 13 Assess Models: ROC Curves
  14. 14 CRISP-DM Step 6: Deployment Steps
  15. 15 Model Results after Deployment
  16. 16 What is Predictive Analytics? Simple Definitions
  17. 17 Predictive Analytics vs. Data Science
  18. 18 What Degree Does it Take to Be a Predictive Modeler?
  19. 19 The Analyst's Journey

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