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001 Basic Search Algorithms - Introduction.en.srt
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001 Basic Search Algorithms - Introduction.mp4
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001 Cross-Validation.en.srt
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001 Cross-Validation.mp4
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001 Introduction.en.srt
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001 Introduction.mp4
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001 Parameters and Hyperparameters.en.srt
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001 Parameters and Hyperparameters.mp4
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001 SMAC.en.srt
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001 SMAC.mp4
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001 Scikit-Optimize.en.srt
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001 Scikit-Optimize.mp4
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001 Sequential Search.en.srt
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001 Sequential Search.mp4
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001 What's next_.html
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002 Bayesian Optimization.en.srt
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002 Bias vs Variance (Optional).html
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002 Classification Metrics (Optional).en.srt
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002 Course Curriculum.mp4
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002 Bayesian Optimization.mp4
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002 Classification Metrics (Optional).mp4
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002 Course Curriculum.en.srt
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002 Hyperparameter Optimization.en.srt
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002 Hyperparameter Optimization.mp4
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002 Manual Search.en.srt
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002 Manual Search.mp4
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002 SMAC Demo.en.srt
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002 SMAC Demo.mp4
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002 Section Content.en.srt
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002 Section Content.mp4
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003 Course aim and knowledge requirements.mp4
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003 Cross-Validation Schemes.en.srt
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003 Cross-Validation Schemes.mp4
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003 Grid Search.mp4
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003 Hyperparameter Distributions.en.srt
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003 Regression Metrics (Optional).en.srt
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003 Bayesian Inference - Introduction.en.srt
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003 Bayesian Inference - Introduction.mp4
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003 Course aim and knowledge requirements.en.srt
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003 Grid Search.en.srt
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003 Hyperparameter Distributions.mp4
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003 Regression Metrics (Optional).mp4
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003 Tree-structured Parzen Estimators - TPE.en.srt
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003 Tree-structured Parzen Estimators - TPE.mp4
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004 Course Material.en.srt
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004 Course Material.mp4
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004 Cross-Validation for model error estimation - Demo.en.srt
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004 Cross-Validation for model error estimation - Demo.mp4
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004 Defining the hyperparameter space.en.srt
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004 Defining the hyperparameter space.mp4
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004 Grid Search - Demo.en.srt
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004 Grid Search - Demo.mp4
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004 Joint and Conditional Probabilities.en.srt
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004 Joint and Conditional Probabilities.mp4
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004 Scikit-learn Metrics.en.srt
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004 Scikit-learn Metrics.mp4
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004 TPE Procedure.en.srt
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004 TPE Procedure.mp4
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005 Bayes Rule.en.srt
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005 Bayes Rule.mp4
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005 Creating your Own Metrics.en.srt
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005 Creating your Own Metrics.mp4
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005 Cross-Validation for Hyperparameter Tuning - Demo.en.srt
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005 Cross-Validation for Hyperparameter Tuning - Demo.mp4
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005 Defining the objective function.en.srt
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005 Defining the objective function.mp4
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005 Grid Search with different hyperparameter spaces.en.srt
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005 Grid Search with different hyperparameter spaces.mp4
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005 Jupyter notebooks.html
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005 TPE hyperparameters.en.srt
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005 TPE hyperparameters.mp4
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006 Presentations.html
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006 Random Search.en.srt
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006 Random Search.mp4
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006 Random search.en.srt
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006 Random search.mp4
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006 Sequential Model-Based Optimization.en.srt
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006 Sequential Model-Based Optimization.mp4
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006 Special Cross-Validation Schemes.en.srt
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006 Special Cross-Validation Schemes.mp4
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006 TPE - why tree-structured_.en.srt
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006 TPE - why tree-structured_.mp4
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006 Using Scikit-learn Metrics.en.srt
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006 Using Scikit-learn Metrics.mp4
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007 Bayesian search with Gaussian processes.en.srt
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007 Bayesian search with Gaussian processes.mp4
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007 Datasets.html
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007 Gaussian Distribution.en.srt
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007 Gaussian Distribution.mp4
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007 Group Cross-Validation - Demo.en.srt
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007 Random Search - Scikit-learn.mp4
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007 Group Cross-Validation - Demo.mp4
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007 Random Search - Scikit-learn.en.srt
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007 TPE with Hyperopt.en.srt
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007 TPE with Hyperopt.mp4
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008 Bayes search with Random Forests.en.srt
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008 Bayes search with Random Forests.mp4
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008 Multivariate Gaussian Distribution.en.srt
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008 Multivariate Gaussian Distribution.mp4
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008 Nested Cross-Validation.en.srt
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008 Nested Cross-Validation.mp4
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008 Random Search with Scikit-Optimize.en.srt
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008 Random Search with Scikit-Optimize.mp4
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008 Set up your computer - required packages.html
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009 Bayes search with GBMs.en.srt
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009 Bayes search with GBMs.mp4
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009 FAQ.html
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009 Gaussian Process.en.srt
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009 Gaussian Process.mp4
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009 Nested Cross-Validation - Demo.en.srt
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009 Nested Cross-Validation - Demo.mp4
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009 Random Search with Hyperopt.en.srt
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009 Random Search with Hyperopt.mp4
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010 Kernels.en.srt
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010 Kernels.mp4
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010 Parallelizing a bayesian search.en.srt
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010 Parallelizing a bayesian search.mp4
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011 Acquisition Functions.en.srt
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011 Acquisition Functions.mp4
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011 Bayesian search with Scikit-learn wrapper.en.srt
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011 Bayesian search with Scikit-learn wrapper.mp4
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012 Additional Reading Resources.html
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012 Changing the kernel of a Gaussian Process.en.srt
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012 Changing the kernel of a Gaussian Process.mp4
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013 Optimizing xgboost.html
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013 Scikit-Optimize - 1-Dimension.en.srt
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013 Scikit-Optimize - 1-Dimension.mp4
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014 Optimizing parameters of a CNN.en.srt
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014 Optimizing parameters of a CNN.mp4
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014 Scikit-Optimize - Manual Search.en.srt
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014 Scikit-Optimize - Manual Search.mp4
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015 Analyzing the CNN search.en.srt
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015 Analyzing the CNN search.mp4
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015 Scikit-Optimize - Automatic Search.en.srt
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015 Scikit-Optimize - Automatic Search.mp4
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016 Scikit-Optimize - Alternative Kernel.en.srt
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016 Scikit-Optimize - Alternative Kernel.mp4
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017 Scikit-Optimize - Neuronal Networks.en.srt
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017 Scikit-Optimize - Neuronal Networks.mp4
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018 Scikit-Optimize - CNN - Search Analysis.en.srt
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018 Scikit-Optimize - CNN - Search Analysis.mp4
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TutsNode.com.txt
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[TGx]Downloaded from torrentgalaxy.to .txt
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