Introduction to Machine Learning: Regression - Part 1

Introduction to Machine Learning: Regression - Part 1

Data Science Festival via YouTube Direct link

Intro

1 of 20

1 of 20

Intro

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Introduction to Machine Learning: Regression - Part 1

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  1. 1 Intro
  2. 2 CONTENTS
  3. 3 ABOUT COMPASS LEXECON
  4. 4 WHAT IS STATISTICAL LEARNING?
  5. 5 VARIOUS APPLICATION OF STATISTICAL LEARNING
  6. 6 HOW-(NON)PARAMETRIC METHODS
  7. 7 WHEN DO WE CARE MORE ABOUT INFERENCE THAN PREDICTION
  8. 8 LINEAR REGRESSION AT COMPASS LEXECON
  9. 9 SIMPLE REGRESSION: PRICE VS COST
  10. 10 WHAT IS THE IMPACT OF COST ON PRICE?
  11. 11 SIMPLE LINEAR REGRESSION MODEL
  12. 12 ESTIMATION OF THE PARAMETERS BY LEAST SQUARES
  13. 13 MULTIPLE REGRESSION: CARTEL EXAMPLE
  14. 14 MULTIPLE REGRESSION AND CARTEL EXAMPLE-DUMMY VARIAB
  15. 15 CARTEL OVERCHARGE-BEFORE-DURING-AFTER COMPARISON
  16. 16 OVERCHARGE-CROSS-SECTIONAL COMPARISON
  17. 17 OVERCHARGE-DIFFERENCE-IN-DIFFERENCES ANALYSIS
  18. 18 INTERPRETING REGRESSION RESULTS
  19. 19 OVERALL MODEL ACCURACY-GOODNESS OF FIT
  20. 20 CONCLUSION: WHAT IS A GOOD MODEL (ACCORDING TO US)?

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