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Deep Learning A-Z™: Regression & Classification - Module 7

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Deep Learning A-Z™: Regression & Classification - Module 7

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Deep Learning A-Z™: Regression & Classification - Module 7

  1. 1. © SuperDataScienceDeep Learning A-Z
  2. 2. © SuperDataScienceDeep Learning A-Z
  3. 3. © SuperDataScienceDeep Learning A-Z Simple Linear Regression y = b0 + b1*x1 Dependent variable (DV) Independent variable (IV) CoefficientConstant
  4. 4. © SuperDataScienceDeep Learning A-Z Simple Linear Regression: Salary ($) Experience y = b0 + b1*x Salary = b0 + b1 *Experience +1yr +10k 30k
  5. 5. © SuperDataScienceDeep Learning A-Z
  6. 6. © SuperDataScienceDeep Learning A-Z Simple Linear Regression: Salary ($) Experience yî yi SUM (y - ŷ )2 -> min
  7. 7. © SuperDataScienceDeep Learning A-Z
  8. 8. © SuperDataScienceDeep Learning A-Z Simple Linear Regression Multiple Linear Regression y = b0 + b1*x1 y = b0 + b1*x1 + b2*x2 + … + bn*xn Dependent variable (DV) Independent variables (IVs) Constant Coefficients
  9. 9. © SuperDataScienceDeep Learning A-Z
  10. 10. © SuperDataScienceDeep Learning A-Z y = b0 + b1*x1 + … + bn*xn Linear Regression: y = b0 + b1*x - Simple: - Multiple:
  11. 11. © SuperDataScienceDeep Learning A-Z We know this:This is new: Salary ($) Experience y = b0 + b1*x?? ? Action (Y/N) Age 0 1 -
  12. 12. © SuperDataScienceDeep Learning A-Z Action (Y/N) Age 0 1 -
  13. 13. © SuperDataScienceDeep Learning A-Z 1 - Action (Y/N) Age 0
  14. 14. © SuperDataScienceDeep Learning A-Z 1 - Action (Y/N) Age 0
  15. 15. © SuperDataScienceDeep Learning A-Z y = b0 + b1*x 1 + e-y 1 p = ln ( ) = b0 + b1*x1 – p p
  16. 16. © SuperDataScienceDeep Learning A-Z
  17. 17. © SuperDataScienceDeep Learning A-Z ln ( ) = b0 + b1*x1 – p p y (Actual DV) X p̂ (Probability) p_hat
  18. 18. © SuperDataScienceDeep Learning A-Z X p̂ (Probability) 20 30 40 50 p̂ =0.7% p̂ =23% p̂ =85% p̂ =99.4% p_hat
  19. 19. © SuperDataScienceDeep Learning A-Z X p̂ (Probability)y (Actual DV) ŷ (Predicted DV) 0.5 ŷ = 0 ŷ = 0 ŷ = 1 ŷ = 1 1 Fin.
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    Dec. 26, 2018

Deep Learning A-Z™: Regression & Classification - Module 7

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