udemy-hyperparameter-optimization-for-machine-learning-2021-5

\ 0:00 Introduction 3:29 Course curriculum 10:06 Course aim and knowledge requirements 12:30 Course material Tuning - Overview\ 0:14:15 Parameters and Hyperparameters 0:25:29 Hyperparameter Optimization metrics\ 34:21 Performance Metrics - Introduction 35:38 Classification Metrics (Optional) 43:46 Regression Metrics (Optional) 47:27 Scikit-learn metrics 53:56 Creating your own metrics 1:03:01 Using Scikit-learn metrics \ 1:04:57 Cross-Validation 1:14:12 Cross-Validation schemes 1:28:07 Estimating the model generalization error with CV - Demo 1:36:42 Cross-Validation for Hyperparameter Tuning - Demo 1:44:15 Special Cross-Validation schemes 1:51:22 Group Cross-Validation - Demo 1:56:26 Nested Cross-Validation 2:03:45 Nested Cross-Validation - Demo Search Algorithms\ 2:10:28 Basic Search Algorithms - Introduction 2:15:38 Manual Search 2:22:13 Grid Search 2:25:34 Grid Search - Demo 2:33:24 Grid Search with different hyperparameter spaces