Nov 2024

22.1. Radial Basis Function (RBF) Kernel

Nov 2024

30. Extreme Gradient Boosting (XGBoost)

Nov 2024

29. Gradient Boosting

Nov 2024

28. Boosting

Nov 2024

27. Sequential Learning

Nov 2024

26. Bagging

Nov 2024

25. Voting

Nov 2024

24.1 Distinguishing between ensembling, hybrid, mixing, and mutating

Nov 2024

24. Ensemble Learning

Nov 2024

23. Weak and Strong Learners

Nov 2024

22. Kernel Support Vector Machine

Nov 2024

21. Soft-max Support Vector Machine

Nov 2024

20. Support Vector Machine

Nov 2024

19. Likelihood Function and Maximum Likelihood Estimation

Nov 2024

18. Decision Tree

Nov 2024

17. Perceptron Learning Algorithms

Nov 2024

16. Sampling Methods

Nov 2024

15. Sigmoid Function

Nov 2024

14. Evaluation Metrics

Nov 2024

13. Noise and Outlier

Nov 2024

12. Classification Model

Nov 2024

11. Entropy

Nov 2024

10. Dataset

Nov 2024

09. Duality

Nov 2024

08. Optimization Problems

Nov 2024

07. Gradient Descent for Multi-Variable Functions

Nov 2024

06. Stochastic Gradient Descent

Nov 2024

05. Gradient Descent

Nov 2024

04. Data Dimension Greater than the Number of Data Points

Nov 2024

03. Matrix Diagonalization and Eigen Decomposition

Nov 2024

02. Convex Functions

Nov 2024

01. Convex Set