Course curriculum

    1. Overview

    2. Prerequisites

    3. File to download

    4. Automate Hyper-Parameter selection

    5. More explanation

    6. Cross Validation

    7. More explanation

    8. Cross Validation Dataset

    9. Documentation

    10. List all parameters

    11. Pipeline Parameters

    12. Parameter Spaces

    13. Add other parameters

    14. Increased Runtime

    15. Challenge Problem

    16. Challenge answer

    17. Use GridSearchCV

    1. Recap

    2. Recap continued

    3. Find best combination

    4. Balanced accuracy

    5. Best parameter values

    6. Range edge values

    7. Summary of results

    8. Best Pipeline

    9. Balance Testing data

    10. Discuss extra parameters

    11. Challenge Problem

    12. Max Features

    13. Try Max Features

    14. Discuss few points

    15. Stabilizing our Model

    16. Random Forest

    17. Visual Representation

    18. Use Random Forest

    19. Challenge Problem

    20. General Suggestion

    21. Congratulations on completing this course!

About this course

  • $295.00
  • 38 lessons
  • 1.5 hours of video content