Udemy - Hyperparameter Optimization for Machine Learning (9.2024)

Creation Time	Sept. 28, 2025, 1:54 a.m.
Last Access Time	Sept. 30, 2025, 8:40 a.m.
File Size	4.1 GB
Keywords	2024 for Hyperparameter - Udemy Machine Optimization Learning 9
Total Requests	22
Total Files	176
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06 - Bayesian Optimization/050 Scikit-Optimize - Neuronal Networks.mp4 171.6 MB
08 - Scikit-Optimize/074 Optimizing Hyperparameters of a CNN.mp4 171.5 MB
07 - Other SMBO Algorithms/054 SMAC Demo.mp4 153.3 MB
06 - Bayesian Optimization/046 Scikit-Optimize - 1-Dimension.mp4 135.8 MB
10 - Optuna/090 Optimizing hyperparameters of a CNN.mp4 131.0 MB
04 - Cross-Validation/019 Cross-Validation schemes.mp4 129.1 MB
09 - Hyperopt/078 Search space configuration and distributions.mp4 121.3 MB
06 - Bayesian Optimization/041 Multivariate Gaussian Distribution.mp4 115.5 MB
06 - Bayesian Optimization/039 Sequential Model-Based Optimization.mp4 112.9 MB
04 - Cross-Validation/020 Estimating the model generalization error with CV - Demo.mp4 111.6 MB
03 - Performance metrics/015 Creating your own metrics.mp4 109.9 MB
06 - Bayesian Optimization/044 Acquisition Functions.mp4 107.7 MB
09 - Hyperopt/080 Search algorithms.mp4 98.6 MB
10 - Optuna/092 Evaluating the search with Optuna's built in functions.mp4 95.1 MB
10 - Optuna/088 Search algorithms.mp4 85.3 MB
05 - Basic Search Algorithms/030 Random Search with Scikit-learn.mp4 83.4 MB
04 - Cross-Validation/023 Group Cross-Validation - Demo.mp4 83.3 MB
04 - Cross-Validation/017 Cross-Validation.mp4 80.4 MB
05 - Basic Search Algorithms/025 Manual Search.mp4 78.7 MB
10 - Optuna/089 Optimizing multiple ML models with simultaneously.mp4 78.1 MB
09 - Hyperopt/082 Optimizing multiple ML models simultaneously.mp4 78.1 MB
04 - Cross-Validation/021 Cross-Validation for Hyperparameter Tuning - Demo.mp4 77.0 MB
07 - Other SMBO Algorithms/059 TPE with Hyperopt.mp4 76.5 MB
05 - Basic Search Algorithms/031 Random Search with Scikit-Optimize.mp4 73.0 MB
09 - Hyperopt/081 Evaluating the search.mp4 65.0 MB
06 - Bayesian Optimization/042 Gaussian Process.mp4 58.5 MB
07 - Other SMBO Algorithms/060 Discussion Bayesian Optimization and Basic Search.mp4 58.4 MB
05 - Basic Search Algorithms/029 Random Search.mp4 57.5 MB
06 - Bayesian Optimization/038 Bayes Rule.mp4 57.3 MB
08 - Scikit-Optimize/066 Random search.mp4 56.1 MB
10 - Optuna/091 Optimizing a CNN - extended.mp4 51.1 MB
06 - Bayesian Optimization/047 Scikit-Optimize - Manual Search.mp4 50.6 MB
08 - Scikit-Optimize/067 Bayesian search with Gaussian processes.mp4 50.1 MB
06 - Bayesian Optimization/051 Scikit-Optimize - CNN - Search Analysis.mp4 46.9 MB
05 - Basic Search Algorithms/027 Grid Search - Demo.mp4 46.2 MB
05 - Basic Search Algorithms/032 Random Search with Hyperopt.mp4 44.9 MB
06 - Bayesian Optimization/036 Bayesian Inference - Introduction.mp4 43.9 MB
08 - Scikit-Optimize/070 Parallelizing a Bayesian search.mp4 40.0 MB
02 - Hyperparameter Tuning - Overview/010 Parameters and Hyperparameters.mp4 38.1 MB
02 - Hyperparameter Tuning - Overview/011 Hyperparameter Optimization.mp4 37.0 MB
06 - Bayesian Optimization/048 Scikit-Optimize - Automatic Search.mp4 36.2 MB
08 - Scikit-Optimize/071 Bayesian search with Scikit-learn wrapper.mp4 36.2 MB
05 - Basic Search Algorithms/024 Basic Search Algorithms - Introduction.mp4 36.2 MB
06 - Bayesian Optimization/035 Bayesian Optimization.mp4 35.4 MB
05 - Basic Search Algorithms/028 Grid Search with different hyperparameter spaces.mp4 34.8 MB
03 - Performance metrics/016 Using Scikit-learn metrics.mp4 34.1 MB
08 - Scikit-Optimize/069 Bayesian search with GBMs.mp4 33.4 MB
10 - Optuna/086 Optuna main functions.mp4 32.7 MB
06 - Bayesian Optimization/034 Sequential Search.mp4 31.9 MB
01 - Introduction/001 Introduction.mp4 30.8 MB
08 - Scikit-Optimize/068 Bayesian search with Random Forests.mp4 30.6 MB
06 - Bayesian Optimization/037 Joint and Conditional Probabilities.mp4 30.4 MB
08 - Scikit-Optimize/072 Changing the kernel of a Gaussian Process.mp4 29.3 MB
06 - Bayesian Optimization/049 Scikit-Optimize - Alternative Kernel.mp4 29.3 MB
03 - Performance metrics/013 Classification Metrics (Optional).mp4 28.8 MB
08 - Scikit-Optimize/063 Hyperparameter Distributions.mp4 27.7 MB
04 - Cross-Validation/022 Special Cross-Validation schemes.mp4 27.0 MB
07 - Other SMBO Algorithms/056 TPE Procedure.mp4 26.7 MB
07 - Other SMBO Algorithms/053 SMAC.mp4 25.5 MB
09 - Hyperopt/076 Hyperopt.mp4 23.5 MB
06 - Bayesian Optimization/040 Gaussian Distribution.mp4 22.4 MB
07 - Other SMBO Algorithms/058 TPE - why tree-structured.mp4 20.5 MB
08 - Scikit-Optimize/075 Analyzing the CNN search.mp4 19.9 MB
06 - Bayesian Optimization/043 Kernels.mp4 19.4 MB
09 - Hyperopt/079 Sampling from nested spaces.mp4 16.8 MB
08 - Scikit-Optimize/061 Scikit-Optimize.mp4 16.2 MB
07 - Other SMBO Algorithms/057 TPE hyperparameters.mp4 15.3 MB
05 - Basic Search Algorithms/026 Grid Search.mp4 14.7 MB
10 - Optuna/085 Optuna.mp4 14.3 MB
07 - Other SMBO Algorithms/055 Tree-structured Parzen Estimators - TPE.mp4 12.6 MB
01 - Introduction/002 Course curriculum.mp4 12.5 MB
07 - Other SMBO Algorithms/052 Other SMBO Algorithms.mp4 11.9 MB
01 - Introduction/003 Course aim and knowledge requirements.mp4 11.8 MB
03 - Performance metrics/014 Regression Metrics (Optional).mp4 11.6 MB
08 - Scikit-Optimize/064 Defining the hyperparameter space.mp4 10.1 MB
08 - Scikit-Optimize/062 Section content.mp4 8.2 MB
08 - Scikit-Optimize/065 Defining the objective function.mp4 6.9 MB
01 - Introduction/004 Course material.mp4 6.4 MB
09 - Hyperopt/077 Section content.mp4 4.7 MB
03 - Performance metrics/012 Performance Metrics - Introduction.mp4 4.1 MB
10 - Optuna/087 Section content.mp4 2.8 MB
06 - Bayesian Optimization/041 Multivariate Gaussian Distribution.srt 23.0 KB
06 - Bayesian Optimization/039 Sequential Model-Based Optimization.srt 22.6 KB
06 - Bayesian Optimization/046 Scikit-Optimize - 1-Dimension.srt 22.1 KB
06 - Bayesian Optimization/050 Scikit-Optimize - Neuronal Networks.srt 20.7 KB
08 - Scikit-Optimize/074 Optimizing Hyperparameters of a CNN.srt 20.7 KB
04 - Cross-Validation/019 Cross-Validation schemes.srt 20.6 KB
09 - Hyperopt/078 Search space configuration and distributions.srt 19.9 KB
06 - Bayesian Optimization/044 Acquisition Functions.srt 18.9 KB
06 - Bayesian Optimization/042 Gaussian Process.srt 18.4 KB
07 - Other SMBO Algorithms/060 Discussion Bayesian Optimization and Basic Search.srt 17.7 KB
06 - Bayesian Optimization/038 Bayes Rule.srt 16.5 KB
07 - Other SMBO Algorithms/054 SMAC Demo.srt 16.1 KB
02 - Hyperparameter Tuning - Overview/010 Parameters and Hyperparameters.srt 15.7 KB
05 - Basic Search Algorithms/032 Random Search with Hyperopt.srt 15.4 KB
10 - Optuna/092 Evaluating the search with Optuna's built in functions.srt 13.8 KB
04 - Cross-Validation/017 Cross-Validation.srt 13.7 KB
10 - Optuna/090 Optimizing hyperparameters of a CNN.srt 13.4 KB
09 - Hyperopt/082 Optimizing multiple ML models simultaneously.srt 13.2 KB
03 - Performance metrics/015 Creating your own metrics.srt 12.7 KB
02 - Hyperparameter Tuning - Overview/011 Hyperparameter Optimization.srt 12.5 KB
04 - Cross-Validation/020 Estimating the model generalization error with CV - Demo.srt 12.5 KB
09 - Hyperopt/081 Evaluating the search.srt 12.4 KB
05 - Basic Search Algorithms/027 Grid Search - Demo.srt 11.7 KB
09 - Hyperopt/076 Hyperopt.srt 11.6 KB
05 - Basic Search Algorithms/031 Random Search with Scikit-Optimize.srt 11.5 KB
04 - Cross-Validation/021 Cross-Validation for Hyperparameter Tuning - Demo.srt 11.5 KB
05 - Basic Search Algorithms/029 Random Search.srt 11.3 KB
09 - Hyperopt/080 Search algorithms.srt 11.1 KB
03 - Performance metrics/013 Classification Metrics (Optional).srt 11.1 KB
06 - Bayesian Optimization/037 Joint and Conditional Probabilities.srt 10.8 KB
07 - Other SMBO Algorithms/056 TPE Procedure.srt 10.7 KB
06 - Bayesian Optimization/036 Bayesian Inference - Introduction.srt 10.6 KB
06 - Bayesian Optimization/040 Gaussian Distribution.srt 10.2 KB
10 - Optuna/089 Optimizing multiple ML models with simultaneously.srt 10.2 KB
05 - Basic Search Algorithms/025 Manual Search.srt 10.1 KB
10 - Optuna/088 Search algorithms.srt 10.1 KB
04 - Cross-Validation/022 Special Cross-Validation schemes.srt 10.1 KB
10 - Optuna/086 Optuna main functions.srt 10.0 KB
01 - Introduction/002 Course curriculum.srt 9.2 KB
06 - Bayesian Optimization/051 Scikit-Optimize - CNN - Search Analysis.srt 9.1 KB
08 - Scikit-Optimize/075 Analyzing the CNN search.srt 9.1 KB
07 - Other SMBO Algorithms/053 SMAC.srt 8.9 KB
06 - Bayesian Optimization/043 Kernels.srt 8.9 KB
07 - Other SMBO Algorithms/059 TPE with Hyperopt.srt 8.8 KB
06 - Bayesian Optimization/047 Scikit-Optimize - Manual Search.srt 8.6 KB
08 - Scikit-Optimize/061 Scikit-Optimize.srt 8.2 KB
06 - Bayesian Optimization/034 Sequential Search.srt 8.1 KB
05 - Basic Search Algorithms/030 Random Search with Scikit-learn.srt 7.9 KB
05 - Basic Search Algorithms/024 Basic Search Algorithms - Introduction.srt 7.7 KB
08 - Scikit-Optimize/066 Random search.srt 7.7 KB
08 - Scikit-Optimize/067 Bayesian search with Gaussian processes.srt 7.7 KB
04 - Cross-Validation/023 Group Cross-Validation - Demo.srt 7.5 KB
06 - Bayesian Optimization/035 Bayesian Optimization.srt 7.0 KB
10 - Optuna/091 Optimizing a CNN - extended.srt 6.6 KB
06 - Bayesian Optimization/048 Scikit-Optimize - Automatic Search.srt 6.4 KB
08 - Scikit-Optimize/071 Bayesian search with Scikit-learn wrapper.srt 6.4 KB
10 - Optuna/085 Optuna.srt 6.4 KB
07 - Other SMBO Algorithms/057 TPE hyperparameters.srt 6.3 KB
08 - Scikit-Optimize/063 Hyperparameter Distributions.srt 6.2 KB
07 - Other SMBO Algorithms/052 Other SMBO Algorithms.srt 6.0 KB
07 - Other SMBO Algorithms/058 TPE - why tree-structured.srt 5.7 KB
09 - Hyperopt/079 Sampling from nested spaces.srt 5.4 KB
06 - Bayesian Optimization/049 Scikit-Optimize - Alternative Kernel.srt 5.2 KB
08 - Scikit-Optimize/072 Changing the kernel of a Gaussian Process.srt 5.2 KB
07 - Other SMBO Algorithms/055 Tree-structured Parzen Estimators - TPE.srt 5.1 KB
05 - Basic Search Algorithms/026 Grid Search.srt 5.1 KB
01 - Introduction/001 Introduction.srt 5.0 KB
03 - Performance metrics/014 Regression Metrics (Optional).srt 4.9 KB
01 - Introduction/009 Resources to learn machine learning skills.html 4.9 KB
08 - Scikit-Optimize/069 Bayesian search with GBMs.srt 4.5 KB
08 - Scikit-Optimize/068 Bayesian search with Random Forests.srt 4.3 KB
08 - Scikit-Optimize/070 Parallelizing a Bayesian search.srt 4.0 KB
11 - Final bonus section/095 Bonus lecture.html 3.8 KB
01 - Introduction/003 Course aim and knowledge requirements.srt 3.6 KB
06 - Bayesian Optimization/045 Additional Reading Resources.html 3.5 KB
08 - Scikit-Optimize/064 Defining the hyperparameter space.srt 3.5 KB
01 - Introduction/005 Jupyter notebooks.html 3.5 KB
05 - Basic Search Algorithms/028 Grid Search with different hyperparameter spaces.srt 3.4 KB
08 - Scikit-Optimize/062 Section content.srt 3.2 KB
01 - Introduction/008 Set up your computer - required packages.html 2.9 KB
05 - Basic Search Algorithms/033 More examples.html 2.9 KB
08 - Scikit-Optimize/065 Defining the objective function.srt 2.9 KB
01 - Introduction/006 Presentations.html 2.8 KB
03 - Performance metrics/016 Using Scikit-learn metrics.srt 2.7 KB
01 - Introduction/007 Datasets.html 2.7 KB
09 - Hyperopt/083 Optimizing Hyperparameters of a CNN.html 2.6 KB
01 - Introduction/004 Course material.srt 2.6 KB
09 - Hyperopt/084 References.html 2.6 KB
08 - Scikit-Optimize/073 Optimizing xgboost.html 2.5 KB
09 - Hyperopt/077 Section content.srt 2.5 KB
10 - Optuna/094 More examples.html 2.4 KB
04 - Cross-Validation/018 Bias vs Variance (Optional).html 2.4 KB
10 - Optuna/093 References.html 2.3 KB
03 - Performance metrics/012 Performance Metrics - Introduction.srt 1.7 KB
10 - Optuna/087 Section content.srt 1.2 KB

Udemy - Hyperparameter Optimization for Machine Learning (9.2024)

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