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Experimental Design for Data Analysis

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File Name
Size
01. Course Overview/01. Course Overview.mp4
3.7 MB
01. Course Overview/01. Course Overview.srt
13 kB
02. Designing an Experiment for Data Analysis/01. Module Overview.mp4
2.0 MB
02. Designing an Experiment for Data Analysis/01. Module Overview.srt
8.6 kB
02. Designing an Experiment for Data Analysis/02. Prerequisites and Course Outline.mp4
1.7 MB
02. Designing an Experiment for Data Analysis/02. Prerequisites and Course Outline.srt
10 kB
02. Designing an Experiment for Data Analysis/03. Connecting the Dots with Data.mp4
4.3 MB
02. Designing an Experiment for Data Analysis/03. Connecting the Dots with Data.srt
23 kB
02. Designing an Experiment for Data Analysis/04. Hypothesis Testing.mp4
12 MB
02. Designing an Experiment for Data Analysis/04. Hypothesis Testing.srt
58 kB
02. Designing an Experiment for Data Analysis/05. T-tests.mp4
5.2 MB
02. Designing an Experiment for Data Analysis/05. T-tests.srt
25 kB
02. Designing an Experiment for Data Analysis/06. ANOVA.mp4
7.6 MB
02. Designing an Experiment for Data Analysis/06. ANOVA.srt
35 kB
02. Designing an Experiment for Data Analysis/07. Designing a Machine Learning Experiment.mp4
8.5 MB
02. Designing an Experiment for Data Analysis/07. Designing a Machine Learning Experiment.srt
42 kB
02. Designing an Experiment for Data Analysis/08. Summary.mp4
2.6 MB
02. Designing an Experiment for Data Analysis/08. Summary.srt
12 kB
03. Building and Training a Machine Learning Model/01. Module Overview.mp4
2.4 MB
03. Building and Training a Machine Learning Model/01. Module Overview.srt
12 kB
03. Building and Training a Machine Learning Model/02. Getting Started with Azure ML Studio.mp4
14 MB
03. Building and Training a Machine Learning Model/02. Getting Started with Azure ML Studio.srt
43 kB
03. Building and Training a Machine Learning Model/03. Loading and Visualizing Data.mp4
12 MB
03. Building and Training a Machine Learning Model/03. Loading and Visualizing Data.srt
45 kB
03. Building and Training a Machine Learning Model/04. Exploring Relationships in Data.mp4
12 MB
03. Building and Training a Machine Learning Model/04. Exploring Relationships in Data.srt
39 kB
03. Building and Training a Machine Learning Model/05. Preprocessing and Preparing Data.mp4
16 MB
03. Building and Training a Machine Learning Model/05. Preprocessing and Preparing Data.srt
49 kB
03. Building and Training a Machine Learning Model/06. Building and Training a Regression Model for Price Prediction.mp4
20 MB
03. Building and Training a Machine Learning Model/06. Building and Training a Regression Model for Price Prediction.srt
67 kB
03. Building and Training a Machine Learning Model/07. Building and Training a Regression Model in Python.mp4
23 MB
03. Building and Training a Machine Learning Model/07. Building and Training a Regression Model in Python.srt
70 kB
03. Building and Training a Machine Learning Model/08. Summary.mp4
2.0 MB
03. Building and Training a Machine Learning Model/08. Summary.srt
10 kB
04. Understanding and Overcoming Common Problems in Data Modeling/01. Module Overview.mp4
1.7 MB
04. Understanding and Overcoming Common Problems in Data Modeling/01. Module Overview.srt
8.8 kB
04. Understanding and Overcoming Common Problems in Data Modeling/02. Overfitting and Techniques to Mitigate Overfitting.mp4
11 MB
04. Understanding and Overcoming Common Problems in Data Modeling/02. Overfitting and Techniques to Mitigate Overfitting.srt
53 kB
04. Understanding and Overcoming Common Problems in Data Modeling/03. Accuracy, Precision, and Recall.mp4
7.8 MB
04. Understanding and Overcoming Common Problems in Data Modeling/03. Accuracy, Precision, and Recall.srt
37 kB
04. Understanding and Overcoming Common Problems in Data Modeling/04. The ROC Curve.mp4
6.2 MB
04. Understanding and Overcoming Common Problems in Data Modeling/04. The ROC Curve.srt
30 kB
04. Understanding and Overcoming Common Problems in Data Modeling/05. Preparing and Processing Data.mp4
19 MB
04. Understanding and Overcoming Common Problems in Data Modeling/05. Preparing and Processing Data.srt
59 kB
04. Understanding and Overcoming Common Problems in Data Modeling/06. Building Training and Evaluating a Classification Model.mp4
20 MB
04. Understanding and Overcoming Common Problems in Data Modeling/06. Building Training and Evaluating a Classification Model.srt
63 kB
04. Understanding and Overcoming Common Problems in Data Modeling/07. Summary.mp4
2.1 MB
04. Understanding and Overcoming Common Problems in Data Modeling/07. Summary.srt
12 kB
05. Leveraging Different Validation Strategies in Data Modeling/01. Module Overview.mp4
2.0 MB
05. Leveraging Different Validation Strategies in Data Modeling/01. Module Overview.srt
8.7 kB
05. Leveraging Different Validation Strategies in Data Modeling/02. Cross-validation in the ML Workflow.mp4
3.5 MB
05. Leveraging Different Validation Strategies in Data Modeling/02. Cross-validation in the ML Workflow.srt
14 kB
05. Leveraging Different Validation Strategies in Data Modeling/03. Singular Cross-validation.mp4
5.1 MB
05. Leveraging Different Validation Strategies in Data Modeling/03. Singular Cross-validation.srt
26 kB
05. Leveraging Different Validation Strategies in Data Modeling/04. Cross-validation Using Azure ML Studio.mp4
16 MB
05. Leveraging Different Validation Strategies in Data Modeling/04. Cross-validation Using Azure ML Studio.srt
43 kB
05. Leveraging Different Validation Strategies in Data Modeling/05. K-fold Cross-validation and Variants.mp4
9.9 MB
05. Leveraging Different Validation Strategies in Data Modeling/05. K-fold Cross-validation and Variants.srt
45 kB
05. Leveraging Different Validation Strategies in Data Modeling/06. K-fold Cross-validation in scikit-learn.mp4
16 MB
05. Leveraging Different Validation Strategies in Data Modeling/06. K-fold Cross-validation in scikit-learn.srt
55 kB
05. Leveraging Different Validation Strategies in Data Modeling/07. Repeated K-fold Cross-validation in scikit-learn.mp4
9.4 MB
05. Leveraging Different Validation Strategies in Data Modeling/07. Repeated K-fold Cross-validation in scikit-learn.srt
31 kB
05. Leveraging Different Validation Strategies in Data Modeling/08. Stratified K-fold Cross-validation in scikit-learn.mp4
13 MB
05. Leveraging Different Validation Strategies in Data Modeling/08. Stratified K-fold Cross-validation in scikit-learn.srt
37 kB
05. Leveraging Different Validation Strategies in Data Modeling/09. Group K-fold in scikit-learn.mp4
8.8 MB
05. Leveraging Different Validation Strategies in Data Modeling/09. Group K-fold in scikit-learn.srt
30 kB
05. Leveraging Different Validation Strategies in Data Modeling/10. Summary.mp4
2.0 MB
05. Leveraging Different Validation Strategies in Data Modeling/10. Summary.srt
9.6 kB
06. Tuning Hyperparameters Using Cross Validation Scores/01. Module Overview.mp4
3.4 MB
06. Tuning Hyperparameters Using Cross Validation Scores/01. Module Overview.srt
16 kB
06. Tuning Hyperparameters Using Cross Validation Scores/02. Hyperparameter Tuning.mp4
3.2 MB
06. Tuning Hyperparameters Using Cross Validation Scores/02. Hyperparameter Tuning.srt
16 kB
06. Tuning Hyperparameters Using Cross Validation Scores/03. Decision Trees.mp4
4.6 MB
06. Tuning Hyperparameters Using Cross Validation Scores/03. Decision Trees.srt
24 kB
06. Tuning Hyperparameters Using Cross Validation Scores/04. Hyperparameter Tuning a Decision Forest Classifier.mp4
17 MB
06. Tuning Hyperparameters Using Cross Validation Scores/04. Hyperparameter Tuning a Decision Forest Classifier.srt
51 kB
06. Tuning Hyperparameters Using Cross Validation Scores/05. Tuning and Scoring Multiple Models.mp4
13 MB
06. Tuning Hyperparameters Using Cross Validation Scores/05. Tuning and Scoring Multiple Models.srt
40 kB
06. Tuning Hyperparameters Using Cross Validation Scores/06. Summary and Further Study.mp4
1.7 MB
06. Tuning Hyperparameters Using Cross Validation Scores/06. Summary and Further Study.srt
9.0 kB
experimental-design-data-analysis.zip
5.2 MB