Course curriculum

    1. DISCLAIMER

    2. Introduction to QT401

    3. Artificial Intelligence is Search

    4. Genetic Programs as Intelligent Systems

    5. GP Iterations

    6. Specifying the Primitive Set

    7. Ephemeral Constant Generation

    8. Brute Force Numerical Trees

    9. Brute Force Boolean Trees

    10. Simulating the Brute Force Alphas

    11. Genetic Operators

    12. Crossover Implementation

    13. Mutation Implementation

    14. GP Implementation Overview

    15. Warm Start Initialization

    16. Elitism

    17. NaN Proof Marginal Significance

    18. Evolution; Recombination

    19. Evolution; Mutation

    20. Simulation Walkthrough

    21. Multi Objective Optimization

    22. k-Pareto Optimality Measure

    23. GP Bloat, Kruskal Wallis and Conover Iman tests

    24. Covariant Parsimony Pressure

    25. Verifying the Parsimony Coefficients

    26. Adding Proprietary Datasets

    27. Advanced GP Extensions

    28. Support and Bug Fix Lecture

About this course

  • $380.00
  • 28 lessons
  • 8.5 hours of video content
  • PREREQS TO: QT101.QT201.QT301