Experimental Design for Data Analysis

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Experimental Design for Data Analysis

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种子哈希：9e737177f3eb98cb7c679c0ae14768f3406c7dcc
文件大小：349.72M
已经下载：2441次
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收录时间：2024-01-05
最近下载：2024-12-09

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文件列表

  • 03. Building and Training a Machine Learning Model/07. Building and Training a Regression Model in Python.mp4 24.4 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/06. Building Training and Evaluating a Classification Model.mp4 21.1 MB
  • 03. Building and Training a Machine Learning Model/06. Building and Training a Regression Model for Price Prediction.mp4 20.8 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/05. Preparing and Processing Data.mp4 19.7 MB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/04. Hyperparameter Tuning a Decision Forest Classifier.mp4 17.8 MB
  • 03. Building and Training a Machine Learning Model/05. Preprocessing and Preparing Data.mp4 16.9 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/06. K-fold Cross-validation in scikit-learn.mp4 16.3 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/04. Cross-validation Using Azure ML Studio.mp4 16.3 MB
  • 03. Building and Training a Machine Learning Model/02. Getting Started with Azure ML Studio.mp4 14.2 MB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/05. Tuning and Scoring Multiple Models.mp4 13.2 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/08. Stratified K-fold Cross-validation in scikit-learn.mp4 13.2 MB
  • 03. Building and Training a Machine Learning Model/03. Loading and Visualizing Data.mp4 13.1 MB
  • 03. Building and Training a Machine Learning Model/04. Exploring Relationships in Data.mp4 12.6 MB
  • 02. Designing an Experiment for Data Analysis/04. Hypothesis Testing.mp4 12.5 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/02. Overfitting and Techniques to Mitigate Overfitting.mp4 11.1 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/05. K-fold Cross-validation and Variants.mp4 10.4 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/07. Repeated K-fold Cross-validation in scikit-learn.mp4 9.9 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/09. Group K-fold in scikit-learn.mp4 9.2 MB
  • 02. Designing an Experiment for Data Analysis/07. Designing a Machine Learning Experiment.mp4 8.9 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/03. Accuracy, Precision, and Recall.mp4 8.2 MB
  • 02. Designing an Experiment for Data Analysis/06. ANOVA.mp4 8.0 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/04. The ROC Curve.mp4 6.5 MB
  • 02. Designing an Experiment for Data Analysis/05. T-tests.mp4 5.4 MB
  • experimental-design-data-analysis.zip 5.4 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/03. Singular Cross-validation.mp4 5.4 MB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/03. Decision Trees.mp4 4.8 MB
  • 02. Designing an Experiment for Data Analysis/03. Connecting the Dots with Data.mp4 4.6 MB
  • 01. Course Overview/01. Course Overview.mp4 3.9 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/02. Cross-validation in the ML Workflow.mp4 3.6 MB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/01. Module Overview.mp4 3.6 MB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/02. Hyperparameter Tuning.mp4 3.3 MB
  • 02. Designing an Experiment for Data Analysis/08. Summary.mp4 2.7 MB
  • 03. Building and Training a Machine Learning Model/01. Module Overview.mp4 2.5 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/07. Summary.mp4 2.2 MB
  • 02. Designing an Experiment for Data Analysis/01. Module Overview.mp4 2.1 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/01. Module Overview.mp4 2.1 MB
  • 05. Leveraging Different Validation Strategies in Data Modeling/10. Summary.mp4 2.1 MB
  • 03. Building and Training a Machine Learning Model/08. Summary.mp4 2.1 MB
  • 02. Designing an Experiment for Data Analysis/02. Prerequisites and Course Outline.mp4 1.8 MB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/06. Summary and Further Study.mp4 1.8 MB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/01. Module Overview.mp4 1.8 MB
  • 03. Building and Training a Machine Learning Model/07. Building and Training a Regression Model in Python.srt 72.0 kB
  • 03. Building and Training a Machine Learning Model/06. Building and Training a Regression Model for Price Prediction.srt 68.2 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/06. Building Training and Evaluating a Classification Model.srt 64.6 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/05. Preparing and Processing Data.srt 60.3 kB
  • 02. Designing an Experiment for Data Analysis/04. Hypothesis Testing.srt 59.1 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/06. K-fold Cross-validation in scikit-learn.srt 56.0 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/02. Overfitting and Techniques to Mitigate Overfitting.srt 54.0 kB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/04. Hyperparameter Tuning a Decision Forest Classifier.srt 52.3 kB
  • 03. Building and Training a Machine Learning Model/05. Preprocessing and Preparing Data.srt 50.0 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/05. K-fold Cross-validation and Variants.srt 46.3 kB
  • 03. Building and Training a Machine Learning Model/03. Loading and Visualizing Data.srt 45.9 kB
  • 03. Building and Training a Machine Learning Model/02. Getting Started with Azure ML Studio.srt 44.2 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/04. Cross-validation Using Azure ML Studio.srt 43.8 kB
  • 02. Designing an Experiment for Data Analysis/07. Designing a Machine Learning Experiment.srt 43.5 kB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/05. Tuning and Scoring Multiple Models.srt 41.0 kB
  • 03. Building and Training a Machine Learning Model/04. Exploring Relationships in Data.srt 39.6 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/08. Stratified K-fold Cross-validation in scikit-learn.srt 37.6 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/03. Accuracy, Precision, and Recall.srt 37.6 kB
  • 02. Designing an Experiment for Data Analysis/06. ANOVA.srt 36.2 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/07. Repeated K-fold Cross-validation in scikit-learn.srt 32.0 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/09. Group K-fold in scikit-learn.srt 31.3 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/04. The ROC Curve.srt 31.2 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/03. Singular Cross-validation.srt 26.8 kB
  • 02. Designing an Experiment for Data Analysis/05. T-tests.srt 25.7 kB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/03. Decision Trees.srt 25.1 kB
  • 02. Designing an Experiment for Data Analysis/03. Connecting the Dots with Data.srt 23.3 kB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/01. Module Overview.srt 16.8 kB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/02. Hyperparameter Tuning.srt 16.2 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/02. Cross-validation in the ML Workflow.srt 14.0 kB
  • 01. Course Overview/01. Course Overview.srt 13.6 kB
  • 03. Building and Training a Machine Learning Model/01. Module Overview.srt 12.4 kB
  • 02. Designing an Experiment for Data Analysis/08. Summary.srt 12.3 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/07. Summary.srt 12.1 kB
  • 03. Building and Training a Machine Learning Model/08. Summary.srt 10.7 kB
  • 02. Designing an Experiment for Data Analysis/02. Prerequisites and Course Outline.srt 10.4 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/10. Summary.srt 9.9 kB
  • 06. Tuning Hyperparameters Using Cross Validation Scores/06. Summary and Further Study.srt 9.2 kB
  • 04. Understanding and Overcoming Common Problems in Data Modeling/01. Module Overview.srt 9.0 kB
  • 05. Leveraging Different Validation Strategies in Data Modeling/01. Module Overview.srt 8.9 kB
  • 02. Designing an Experiment for Data Analysis/01. Module Overview.srt 8.8 kB

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