Udemy A Z Machine Learning using Azure Machine Learning AzureML FTU
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Udemy A Z Machine Learning using Azure Machine Learning AzureML FTU
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Udemy A Z Machine Learning using Azure Machine Learning AzureML FTU
0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url -
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How you can help Team-FTU.txt -
1. What You Will Learn in This Section.mp4 -
1. What You Will Learn in This Section.srt -
1. What You Will Learn in This Section.vtt -
2. The course slides for all sections.html -
2.1 Section 01 - Basics of Machine Learning.pdf.pdf -
2.10 Section 05 - Tune Hyperparameter.pdf.pdf -
2.11 Section 11 - Recommendation System.pdf.pdf -
2.12 Section 10 - Feature Selection.pdf.pdf -
2.13 Section 03 - Data Pre-processing.pdf.pdf -
2.14 Section 09 - Data Processing.pdf.pdf -
2.2 Section 06 - Deploy Webservice.pdf.pdf -
2.3 Section - Text Analytics.pdf.pdf -
2.4 Section 02 - Getting Started with AzureML.pdf.pdf -
2.5 Section 07 - Regression.pdf.pdf -
2.6 Section 04 - Classification - 001 - Logistic Regression.pdf.pdf -
2.7 Section 08 - Clustering.pdf.pdf -
2.8 Section 04 - Classification - 003 - SVM.pdf.pdf -
2.9 Section 04 - Classification - 002 - Decision Tree.pdf.pdf -
3. Important Message About Udemy Reviews.mp4 -
3. Important Message About Udemy Reviews.srt -
3. Important Message About Udemy Reviews.vtt -
4. Why Machine Learning is the Future.mp4 -
4. Why Machine Learning is the Future.srt -
4. Why Machine Learning is the Future.vtt -
5. What is Machine Learning.mp4 -
5. What is Machine Learning.srt -
5. What is Machine Learning.vtt -
6. Understanding various aspects of data - Type, Variables, Category.mp4 -
6. Understanding various aspects of data - Type, Variables, Category.srt -
6. Understanding various aspects of data - Type, Variables, Category.vtt -
7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.mp4 -
7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.srt -
7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.vtt -
8. Types of Machine Learning Models - Classification, Regression, Clustering etc.mp4 -
8. Types of Machine Learning Models - Classification, Regression, Clustering etc.srt -
8. Types of Machine Learning Models - Classification, Regression, Clustering etc.vtt -
9. Basics of Machine Learning.html -
1. Feature Selection - Section Introduction.mp4 -
1. Feature Selection - Section Introduction.srt -
1. Feature Selection - Section Introduction.vtt -
2. Pearson Correlation Coefficient.mp4 -
2. Pearson Correlation Coefficient.srt -
2. Pearson Correlation Coefficient.vtt -
3. Chi Square Test of Independence.mp4 -
3. Chi Square Test of Independence.srt -
3. Chi Square Test of Independence.vtt -
4. Kendall Correlation Coefficient.mp4 -
4. Kendall Correlation Coefficient.srt -
4. Kendall Correlation Coefficient.vtt -
5. Spearman's Rank Correlation.mp4 -
5. Spearman's Rank Correlation.srt -
5. Spearman's Rank Correlation.vtt -
6. [Hands On] - Comparison Experiment for Correlation Coefficients.mp4 -
6. [Hands On] - Comparison Experiment for Correlation Coefficients.srt -
6. [Hands On] - Comparison Experiment for Correlation Coefficients.vtt -
7. [Hands On] - Filter Based Selection - AzureML Experiment.mp4 -
7. [Hands On] - Filter Based Selection - AzureML Experiment.srt -
7. [Hands On] - Filter Based Selection - AzureML Experiment.vtt -
8. Fisher Based LDA - Intuition.mp4 -
8. Fisher Based LDA - Intuition.srt -
8. Fisher Based LDA - Intuition.vtt -
9. [Hands On] - Fisher Based LDA - Experiment.mp4 -
9. [Hands On] - Fisher Based LDA - Experiment.srt -
9. [Hands On] - Fisher Based LDA - Experiment.vtt -
9.1 Wine-Low-Medium-High.csv.csv -
1. What is a Recommendation System.mp4 -
1. What is a Recommendation System.srt -
1. What is a Recommendation System.vtt -
2. Data Preparation using Recommender Split.mp4 -
2. Data Preparation using Recommender Split.srt -
2. Data Preparation using Recommender Split.vtt -
3. What is Matchbox Recommender and Train Matchbox Recommender.mp4 -
3. What is Matchbox Recommender and Train Matchbox Recommender.srt -
3. What is Matchbox Recommender and Train Matchbox Recommender.vtt -
4. How to Score the Matchbox Recommender.mp4 -
4. How to Score the Matchbox Recommender.srt -
4. How to Score the Matchbox Recommender.vtt -
5. [Hands On] - Restaurant Recommendation Experiment.mp4 -
5. [Hands On] - Restaurant Recommendation Experiment.srt -
5. [Hands On] - Restaurant Recommendation Experiment.vtt -
6. Understanding the Matchbox Recommendation Results.mp4 -
6. Understanding the Matchbox Recommendation Results.srt -
6. Understanding the Matchbox Recommendation Results.vtt -
7. Recommendation System.html -
1. What is Text Analytics or Natural Language Processing.mp4 -
1. What is Text Analytics or Natural Language Processing.srt -
1. What is Text Analytics or Natural Language Processing.vtt -
2. Text Pre-Processing.mp4 -
2. Text Pre-Processing.srt -
2. Text Pre-Processing.vtt -
3. Bag Of Words and N-Gram Models for Text features.mp4 -
3. Bag Of Words and N-Gram Models for Text features.srt -
3. Bag Of Words and N-Gram Models for Text features.vtt -
4. Feature Hashing.mp4 -
4. Feature Hashing.srt -
4. Feature Hashing.vtt -
5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4 -
5. [Hands On] - Classify Customer Complaints using Text Analytics.srt -
5. [Hands On] - Classify Customer Complaints using Text Analytics.vtt -
5.1 two-class complaints modified.txt.txt -
1. Way Forward.mp4 -
1. Way Forward.srt -
1. Way Forward.vtt -
1.1 Links for datasets.pdf.pdf -
2. Bonus Lecture.html -
1. What You Will Learn in This Section.mp4 -
1. What You Will Learn in This Section.srt -
1. What You Will Learn in This Section.vtt -
2. What is Azure ML and high level architecture..mp4 -
2. What is Azure ML and high level architecture..srt -
2. What is Azure ML and high level architecture..vtt -
3. Creating a Free Azure ML Account.mp4 -
3. Creating a Free Azure ML Account.srt -
3. Creating a Free Azure ML Account.vtt -
4. Azure ML Studio Overview and walk-through.mp4 -
4. Azure ML Studio Overview and walk-through.srt -
4. Azure ML Studio Overview and walk-through.vtt -
5. Azure ML Experiment Workflow.mp4 -
5. Azure ML Experiment Workflow.srt -
5. Azure ML Experiment Workflow.vtt -
6. Azure ML Cheat Sheet for Model Selection.mp4 -
6. Azure ML Cheat Sheet for Model Selection.srt -
6. Azure ML Cheat Sheet for Model Selection.vtt -
6.1 ml_studio_overview_v1.1.pdf.pdf -
6.2 microsoft-machine-learning-algorithm-cheat-sheet-v6.pdf.pdf -
7. Getting Started with AzureML.html -
1. [Hands On] - Data Input-Output - Upload Data.mp4 -
1. [Hands On] - Data Input-Output - Upload Data.srt -
1. [Hands On] - Data Input-Output - Upload Data.vtt -
1.1 Employee Dataset - Full.csv.csv -
2. [Hands On] - Data Input-Output - Convert and Unpack.mp4 -
2. [Hands On] - Data Input-Output - Convert and Unpack.srt -
2. [Hands On] - Data Input-Output - Convert and Unpack.vtt -
2.1 Employee Dataset - Full.zip.zip -
3. [Hands On] - Data Input-Output - Import Data.mp4 -
3. [Hands On] - Data Input-Output - Import Data.srt -
3. [Hands On] - Data Input-Output - Import Data.vtt -
3.1 Adult Dataset URL.txt.txt -
4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp4 -
4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.srt -
4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.vtt -
4.1 Employee Dataset - TSV.txt.txt -
4.2 Employee Dataset - AR2.csv.csv -
4.3 Employee Dataset - AC2.csv.csv -
4.4 Employee Dataset - AR1.csv.csv -
4.5 Employee Dataset - AC1.csv.csv -
5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4 -
5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.srt -
5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.vtt -
5.1 Wine Quality Dataset.csv.csv -
5.2 SQL Statement - Wine.txt.txt -
6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4 -
6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.srt -
6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.vtt -
7. Data Processing.html -
1. Logistic Regression - What is Logistic Regression.mp4 -
1. Logistic Regression - What is Logistic Regression.srt -
1. Logistic Regression - What is Logistic Regression.vtt -
10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.mp4 -
10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.srt -
10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.vtt -
10.1 Bank Telemarketing.csv.csv -
11. Decision Forest - Parameters Explained.mp4 -
11. Decision Forest - Parameters Explained.srt -
11. Decision Forest - Parameters Explained.vtt -
12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4 -
12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.srt -
12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.vtt -
13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.mp4 -
13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.srt -
13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.vtt -
13.1 IRIS Dataset Link.txt.txt -
14. SVM - What is Support Vector Machine.mp4 -
14. SVM - What is Support Vector Machine.srt -
14. SVM - What is Support Vector Machine.vtt -
15. [Hands On] - SVM - Adult Census Income Prediction.mp4 -
15. [Hands On] - SVM - Adult Census Income Prediction.srt -
15. [Hands On] - SVM - Adult Census Income Prediction.vtt -
16. Classification Quiz.html -
2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4 -
2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.srt -
2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.vtt -
2.1 Loan Approval Prediction.csv.csv -
3. Logistic Regression - Understand Parameters and Their Impact.mp4 -
3. Logistic Regression - Understand Parameters and Their Impact.srt -
3. Logistic Regression - Understand Parameters and Their Impact.vtt -
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4 -
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.srt -
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.vtt -
4.1 004 - Logistic Regression - Understanding the results.xlsx.xlsx -
5. Logistic Regression - Model Selection and Impact Analysis.mp4 -
5. Logistic Regression - Model Selection and Impact Analysis.srt -
5. Logistic Regression - Model Selection and Impact Analysis.vtt -
6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.mp4 -
6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.srt -
6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.vtt -
6.1 winequality-red.csv.csv -
7. Decision Tree - What is Decision Tree.mp4 -
7. Decision Tree - What is Decision Tree.srt -
7. Decision Tree - What is Decision Tree.vtt -
8. Decision Tree - Ensemble Learning - Bagging and Boosting.mp4 -
8. Decision Tree - Ensemble Learning - Bagging and Boosting.srt -
8. Decision Tree - Ensemble Learning - Bagging and Boosting.vtt -
9. Decision Tree - Parameters - Two Class Boosted Decision Tree.mp4 -
9. Decision Tree - Parameters - Two Class Boosted Decision Tree.srt -
9. Decision Tree - Parameters - Two Class Boosted Decision Tree.vtt -
1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.mp4 -
1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.srt -
1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.vtt -
2. Hyperparameter Tuning.html -
1. Azure ML Webservice - Prepare the experiment for webservice.mp4 -
1. Azure ML Webservice - Prepare the experiment for webservice.srt -
1. Azure ML Webservice - Prepare the experiment for webservice.vtt -
2. [Hands On] - Deploy Machine Learning Model As a Web Service.mp4 -
2. [Hands On] - Deploy Machine Learning Model As a Web Service.srt -
2. [Hands On] - Deploy Machine Learning Model As a Web Service.vtt -
3. [Hands On] - Use the Web Service - Example of Excel.mp4 -
3. [Hands On] - Use the Web Service - Example of Excel.srt -
3. [Hands On] - Use the Web Service - Example of Excel.vtt -
4. AzureML Web Service.html -
1. What is Linear Regression.mp4 -
1. What is Linear Regression.srt -
1. What is Linear Regression.vtt -
10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.mp4 -
10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.srt -
10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.vtt -
11. Regression Analysis.html -
2. Regression Analysis - Common Metrics.mp4 -
2. Regression Analysis - Common Metrics.srt -
2. Regression Analysis - Common Metrics.vtt -
3. [Hands On] - Linear Regression model using OLS.mp4 -
3. [Hands On] - Linear Regression model using OLS.srt -
3. [Hands On] - Linear Regression model using OLS.vtt -
4. [Hands On] - Linear Regression - R Squared.mp4 -
4. [Hands On] - Linear Regression - R Squared.srt -
4. [Hands On] - Linear Regression - R Squared.vtt -
5. Gradient Descent.mp4 -
5. Gradient Descent.srt -
5. Gradient Descent.vtt -
6. Linear Regression Online Gradient Descent.mp4 -
6. Linear Regression Online Gradient Descent.srt -
6. Linear Regression Online Gradient Descent.vtt -
7. [Hands On] - Experiment Online Gradient.mp4 -
7. [Hands On] - Experiment Online Gradient.srt -
7. [Hands On] - Experiment Online Gradient.vtt -
8. Decision Tree - What is Regression Tree.mp4 -
8. Decision Tree - What is Regression Tree.srt -
8. Decision Tree - What is Regression Tree.vtt -
9. Decision Tree - What is Boosted Decision Tree Regression.mp4 -
9. Decision Tree - What is Boosted Decision Tree Regression.srt -
9. Decision Tree - What is Boosted Decision Tree Regression.vtt -
1. What is Cluster Analysis.mp4 -
1. What is Cluster Analysis.srt -
1. What is Cluster Analysis.vtt -
2. [Hands On] - Cluster Analysis Experiment 1.mp4 -
2. [Hands On] - Cluster Analysis Experiment 1.srt -
2. [Hands On] - Cluster Analysis Experiment 1.vtt -
2.1 Callcenter Data.csv.csv -
3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.mp4 -
3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.srt -
3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.vtt -
4. Clustering or Cluster Analysis.html -
1. Section Introduction.mp4 -
1. Section Introduction.srt -
1. Section Introduction.vtt -
10. Data Normalization - Scale and Reduce.mp4 -
10. Data Normalization - Scale and Reduce.srt -
10. Data Normalization - Scale and Reduce.vtt -
11. [Hands On] - Data Normalization.mp4 -
11. [Hands On] - Data Normalization.srt -
11. [Hands On] - Data Normalization.vtt -
12. PCA - What is PCA and Curse of Dimensionality.mp4 -
12. PCA - What is PCA and Curse of Dimensionality.srt -
12. PCA - What is PCA and Curse of Dimensionality.vtt -
13. [Hands On] - Principal Component Analysis.mp4 -
13. [Hands On] - Principal Component Analysis.srt -
13. [Hands On] - Principal Component Analysis.vtt -
14. Join Data - Join Multiple Datasets based on common keys.mp4 -
14. Join Data - Join Multiple Datasets based on common keys.srt -
14. Join Data - Join Multiple Datasets based on common keys.vtt -
15. [Hands On] - Join Data - Experiment.mp4 -
15. [Hands On] - Join Data - Experiment.srt -
15. [Hands On] - Join Data - Experiment.vtt -
15.1 EmpSalaryJC.csv.csv -
15.2 EmpDeptJC.csv.csv -
2. How to Summarize Data.mp4 -
2. How to Summarize Data.srt -
2. How to Summarize Data.vtt -
3. [Hands On] - Summarize Data - Experiment.mp4 -
3. [Hands On] - Summarize Data - Experiment.srt -
3. [Hands On] - Summarize Data - Experiment.vtt -
4. Outliers Treatment - Clip Values.mp4 -
4. Outliers Treatment - Clip Values.srt -
4. Outliers Treatment - Clip Values.vtt -
5. [Hands On] - Outliers Treatment - Clip Values.mp4 -
5. [Hands On] - Outliers Treatment - Clip Values.srt -
5. [Hands On] - Outliers Treatment - Clip Values.vtt -
6. Clean Missing Data with MICE.mp4 -
6. Clean Missing Data with MICE.srt -
6. Clean Missing Data with MICE.vtt -
7. [Hands On] - Clean Missing Data with MICE.mp4 -
7. [Hands On] - Clean Missing Data with MICE.srt -
7. [Hands On] - Clean Missing Data with MICE.vtt -
7.1 MICE Loan Dataset.csv.csv -
8. SMOTE - Create New Synthetic Observations.mp4 -
8. SMOTE - Create New Synthetic Observations.srt -
8. SMOTE - Create New Synthetic Observations.vtt -
9. [Hands On] - SMOTE.mp4 -
9. [Hands On] - SMOTE.srt -
9. [Hands On] - SMOTE.vtt -
9.1 LoanSMOTE.csv.csv -
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0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url -
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1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url -
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2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url -
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4. (FTUApps.com) Download Cracked Developers Applications For Free.url -
239 bytes
How you can help Team-FTU.txt -
229 bytes
1. What You Will Learn in This Section.mp4 -
19.2 MB
1. What You Will Learn in This Section.srt -
2.6 KB
1. What You Will Learn in This Section.vtt -
2.3 KB
2. The course slides for all sections.html -
336 bytes
2.1 Section 01 - Basics of Machine Learning.pdf.pdf -
1.8 MB
2.10 Section 05 - Tune Hyperparameter.pdf.pdf -
1.2 MB
2.11 Section 11 - Recommendation System.pdf.pdf -
3.1 MB
2.12 Section 10 - Feature Selection.pdf.pdf -
2.9 MB
2.13 Section 03 - Data Pre-processing.pdf.pdf -
1.0 MB
2.14 Section 09 - Data Processing.pdf.pdf -
2.8 MB
2.2 Section 06 - Deploy Webservice.pdf.pdf -
702.4 KB
2.3 Section - Text Analytics.pdf.pdf -
2.0 MB
2.4 Section 02 - Getting Started with AzureML.pdf.pdf -
2.7 MB
2.5 Section 07 - Regression.pdf.pdf -
2.8 MB
2.6 Section 04 - Classification - 001 - Logistic Regression.pdf.pdf -
1.4 MB
2.7 Section 08 - Clustering.pdf.pdf -
1.5 MB
2.8 Section 04 - Classification - 003 - SVM.pdf.pdf -
1.1 MB
2.9 Section 04 - Classification - 002 - Decision Tree.pdf.pdf -
3.4 MB
3. Important Message About Udemy Reviews.mp4 -
19.2 MB
3. Important Message About Udemy Reviews.srt -
4.2 KB
3. Important Message About Udemy Reviews.vtt -
3.7 KB
4. Why Machine Learning is the Future.mp4 -
68.7 MB
4. Why Machine Learning is the Future.srt -
10.1 KB
4. Why Machine Learning is the Future.vtt -
9.2 KB
5. What is Machine Learning.mp4 -
18.5 MB
5. What is Machine Learning.srt -
10.7 KB
5. What is Machine Learning.vtt -
9.7 KB
6. Understanding various aspects of data - Type, Variables, Category.mp4 -
13.6 MB
6. Understanding various aspects of data - Type, Variables, Category.srt -
7.9 KB
6. Understanding various aspects of data - Type, Variables, Category.vtt -
7.1 KB
7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.mp4 -
13.3 MB
7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.srt -
8.3 KB
7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.vtt -
7.5 KB
8. Types of Machine Learning Models - Classification, Regression, Clustering etc.mp4 -
19.0 MB
8. Types of Machine Learning Models - Classification, Regression, Clustering etc.srt -
10.0 KB
8. Types of Machine Learning Models - Classification, Regression, Clustering etc.vtt -
9.2 KB
9. Basics of Machine Learning.html -
140 bytes
1. Feature Selection - Section Introduction.mp4 -
7.7 MB
1. Feature Selection - Section Introduction.srt -
6.9 KB
1. Feature Selection - Section Introduction.vtt -
6.2 KB
2. Pearson Correlation Coefficient.mp4 -
47.2 MB
2. Pearson Correlation Coefficient.srt -
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2. Pearson Correlation Coefficient.vtt -
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3. Chi Square Test of Independence.mp4 -
8.3 MB
3. Chi Square Test of Independence.srt -
6.0 KB
3. Chi Square Test of Independence.vtt -
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4. Kendall Correlation Coefficient.mp4 -
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4. Kendall Correlation Coefficient.srt -
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4. Kendall Correlation Coefficient.vtt -
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5. Spearman's Rank Correlation.mp4 -
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5. Spearman's Rank Correlation.srt -
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5. Spearman's Rank Correlation.vtt -
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6. [Hands On] - Comparison Experiment for Correlation Coefficients.mp4 -
13.2 MB
6. [Hands On] - Comparison Experiment for Correlation Coefficients.srt -
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6. [Hands On] - Comparison Experiment for Correlation Coefficients.vtt -
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7. [Hands On] - Filter Based Selection - AzureML Experiment.mp4 -
6.4 MB
7. [Hands On] - Filter Based Selection - AzureML Experiment.srt -
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7. [Hands On] - Filter Based Selection - AzureML Experiment.vtt -
3.5 KB
8. Fisher Based LDA - Intuition.mp4 -
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8. Fisher Based LDA - Intuition.srt -
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8. Fisher Based LDA - Intuition.vtt -
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9. [Hands On] - Fisher Based LDA - Experiment.mp4 -
61.1 MB
9. [Hands On] - Fisher Based LDA - Experiment.srt -
6.5 KB
9. [Hands On] - Fisher Based LDA - Experiment.vtt -
5.8 KB
9.1 Wine-Low-Medium-High.csv.csv -
95.4 KB
1. What is a Recommendation System.mp4 -
35.0 MB
1. What is a Recommendation System.srt -
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1. What is a Recommendation System.vtt -
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2. Data Preparation using Recommender Split.mp4 -
14.9 MB
2. Data Preparation using Recommender Split.srt -
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2. Data Preparation using Recommender Split.vtt -
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3. What is Matchbox Recommender and Train Matchbox Recommender.mp4 -
14.6 MB
3. What is Matchbox Recommender and Train Matchbox Recommender.srt -
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3. What is Matchbox Recommender and Train Matchbox Recommender.vtt -
7.3 KB
4. How to Score the Matchbox Recommender.mp4 -
10.9 MB
4. How to Score the Matchbox Recommender.srt -
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4. How to Score the Matchbox Recommender.vtt -
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5. [Hands On] - Restaurant Recommendation Experiment.mp4 -
36.2 MB
5. [Hands On] - Restaurant Recommendation Experiment.srt -
12.6 KB
5. [Hands On] - Restaurant Recommendation Experiment.vtt -
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6. Understanding the Matchbox Recommendation Results.mp4 -
17.4 MB
6. Understanding the Matchbox Recommendation Results.srt -
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6. Understanding the Matchbox Recommendation Results.vtt -
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7. Recommendation System.html -
141 bytes
1. What is Text Analytics or Natural Language Processing.mp4 -
44.8 MB
1. What is Text Analytics or Natural Language Processing.srt -
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1. What is Text Analytics or Natural Language Processing.vtt -
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2. Text Pre-Processing.mp4 -
54.6 MB
2. Text Pre-Processing.srt -
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2. Text Pre-Processing.vtt -
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3. Bag Of Words and N-Gram Models for Text features.mp4 -
50.0 MB
3. Bag Of Words and N-Gram Models for Text features.srt -
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3. Bag Of Words and N-Gram Models for Text features.vtt -
7.6 KB
4. Feature Hashing.mp4 -
75.2 MB
4. Feature Hashing.srt -
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4. Feature Hashing.vtt -
12.7 KB
5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4 -
87.4 MB
5. [Hands On] - Classify Customer Complaints using Text Analytics.srt -
11.0 KB
5. [Hands On] - Classify Customer Complaints using Text Analytics.vtt -
9.6 KB
5.1 two-class complaints modified.txt.txt -
47.4 KB
1. Way Forward.mp4 -
50.0 MB
1. Way Forward.srt -
5.4 KB
1. Way Forward.vtt -
4.9 KB
1.1 Links for datasets.pdf.pdf -
261.4 KB
2. Bonus Lecture.html -
6.9 KB
1. What You Will Learn in This Section.mp4 -
13.6 MB
1. What You Will Learn in This Section.srt -
2.3 KB
1. What You Will Learn in This Section.vtt -
2.1 KB
2. What is Azure ML and high level architecture..mp4 -
23.2 MB
2. What is Azure ML and high level architecture..srt -
3.8 KB
2. What is Azure ML and high level architecture..vtt -
3.5 KB
3. Creating a Free Azure ML Account.mp4 -
13.4 MB
3. Creating a Free Azure ML Account.srt -
2.4 KB
3. Creating a Free Azure ML Account.vtt -
2.2 KB
4. Azure ML Studio Overview and walk-through.mp4 -
12.2 MB
4. Azure ML Studio Overview and walk-through.srt -
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4. Azure ML Studio Overview and walk-through.vtt -
4.5 KB
5. Azure ML Experiment Workflow.mp4 -
13.2 MB
5. Azure ML Experiment Workflow.srt -
7.4 KB
5. Azure ML Experiment Workflow.vtt -
6.7 KB
6. Azure ML Cheat Sheet for Model Selection.mp4 -
11.3 MB
6. Azure ML Cheat Sheet for Model Selection.srt -
6.4 KB
6. Azure ML Cheat Sheet for Model Selection.vtt -
5.8 KB
6.1 ml_studio_overview_v1.1.pdf.pdf -
2.2 MB
6.2 microsoft-machine-learning-algorithm-cheat-sheet-v6.pdf.pdf -
404.1 KB
7. Getting Started with AzureML.html -
140 bytes
1. [Hands On] - Data Input-Output - Upload Data.mp4 -
51.0 MB
1. [Hands On] - Data Input-Output - Upload Data.srt -
7.9 KB
1. [Hands On] - Data Input-Output - Upload Data.vtt -
7.2 KB
1.1 Employee Dataset - Full.csv.csv -
1.9 KB
2. [Hands On] - Data Input-Output - Convert and Unpack.mp4 -
22.1 MB
2. [Hands On] - Data Input-Output - Convert and Unpack.srt -
9.0 KB
2. [Hands On] - Data Input-Output - Convert and Unpack.vtt -
8.1 KB
2.1 Employee Dataset - Full.zip.zip -
773 bytes
3. [Hands On] - Data Input-Output - Import Data.mp4 -
13.1 MB
3. [Hands On] - Data Input-Output - Import Data.srt -
6.4 KB
3. [Hands On] - Data Input-Output - Import Data.vtt -
5.7 KB
3.1 Adult Dataset URL.txt.txt -
74 bytes
4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp4 -
26.5 MB
4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.srt -
11.5 KB
4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.vtt -
10.3 KB
4.1 Employee Dataset - TSV.txt.txt -
1.9 KB
4.2 Employee Dataset - AR2.csv.csv -
1.3 KB
4.3 Employee Dataset - AC2.csv.csv -
260 bytes
4.4 Employee Dataset - AR1.csv.csv -
672 bytes
4.5 Employee Dataset - AC1.csv.csv -
1.6 KB
5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4 -
38.9 MB
5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.srt -
18.0 KB
5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.vtt -
16.2 KB
5.1 Wine Quality Dataset.csv.csv -
83.7 KB
5.2 SQL Statement - Wine.txt.txt -
141 bytes
6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4 -
35.5 MB
6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.srt -
16.1 KB
6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.vtt -
14.5 KB
7. Data Processing.html -
140 bytes
1. Logistic Regression - What is Logistic Regression.mp4 -
30.7 MB
1. Logistic Regression - What is Logistic Regression.srt -
6.4 KB
1. Logistic Regression - What is Logistic Regression.vtt -
5.8 KB
10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.mp4 -
25.2 MB
10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.srt -
9.9 KB
10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.vtt -
9.0 KB
10.1 Bank Telemarketing.csv.csv -
4.7 MB
11. Decision Forest - Parameters Explained.mp4 -
5.8 MB
11. Decision Forest - Parameters Explained.srt -
3.8 KB
11. Decision Forest - Parameters Explained.vtt -
3.4 KB
12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4 -
35.1 MB
12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.srt -
13.9 KB
12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.vtt -
12.5 KB
13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.mp4 -
18.6 MB
13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.srt -
7.9 KB
13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.vtt -
7.0 KB
13.1 IRIS Dataset Link.txt.txt -
74 bytes
14. SVM - What is Support Vector Machine.mp4 -
14.9 MB
14. SVM - What is Support Vector Machine.srt -
3.7 KB
14. SVM - What is Support Vector Machine.vtt -
3.2 KB
15. [Hands On] - SVM - Adult Census Income Prediction.mp4 -
13.8 MB
15. [Hands On] - SVM - Adult Census Income Prediction.srt -
5.5 KB
15. [Hands On] - SVM - Adult Census Income Prediction.vtt -
5.0 KB
16. Classification Quiz.html -
140 bytes
2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4 -
52.2 MB
2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.srt -
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2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.vtt -
19.8 KB
2.1 Loan Approval Prediction.csv.csv -
37.1 KB
3. Logistic Regression - Understand Parameters and Their Impact.mp4 -
19.5 MB
3. Logistic Regression - Understand Parameters and Their Impact.srt -
12.5 KB
3. Logistic Regression - Understand Parameters and Their Impact.vtt -
11.3 KB
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4 -
29.4 MB
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.srt -
13.1 KB
4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.vtt -
11.9 KB
4.1 004 - Logistic Regression - Understanding the results.xlsx.xlsx -
24.0 KB
5. Logistic Regression - Model Selection and Impact Analysis.mp4 -
13.8 MB
5. Logistic Regression - Model Selection and Impact Analysis.srt -
5.6 KB
5. Logistic Regression - Model Selection and Impact Analysis.vtt -
5.0 KB
6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.mp4 -
19.7 MB
6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.srt -
8.4 KB
6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.vtt -
7.5 KB
6.1 winequality-red.csv.csv -
83.7 KB
7. Decision Tree - What is Decision Tree.mp4 -
14.3 MB
7. Decision Tree - What is Decision Tree.srt -
7.8 KB
7. Decision Tree - What is Decision Tree.vtt -
7.0 KB
8. Decision Tree - Ensemble Learning - Bagging and Boosting.mp4 -
12.9 MB
8. Decision Tree - Ensemble Learning - Bagging and Boosting.srt -
7.3 KB
8. Decision Tree - Ensemble Learning - Bagging and Boosting.vtt -
6.6 KB
9. Decision Tree - Parameters - Two Class Boosted Decision Tree.mp4 -
12.1 MB
9. Decision Tree - Parameters - Two Class Boosted Decision Tree.srt -
5.9 KB
9. Decision Tree - Parameters - Two Class Boosted Decision Tree.vtt -
5.4 KB
1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.mp4 -
21.9 MB
1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.srt -
9.6 KB
1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.vtt -
8.7 KB
2. Hyperparameter Tuning.html -
140 bytes
1. Azure ML Webservice - Prepare the experiment for webservice.mp4 -
5.6 MB
1. Azure ML Webservice - Prepare the experiment for webservice.srt -
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2.3 KB
2. [Hands On] - Deploy Machine Learning Model As a Web Service.mp4 -
9.2 MB
2. [Hands On] - Deploy Machine Learning Model As a Web Service.srt -
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2. [Hands On] - Deploy Machine Learning Model As a Web Service.vtt -
3.1 KB
3. [Hands On] - Use the Web Service - Example of Excel.mp4 -
16.6 MB
3. [Hands On] - Use the Web Service - Example of Excel.srt -
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3. [Hands On] - Use the Web Service - Example of Excel.vtt -
6.1 KB
4. AzureML Web Service.html -
141 bytes
1. What is Linear Regression.mp4 -
14.0 MB
1. What is Linear Regression.srt -
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1. What is Linear Regression.vtt -
5.3 KB
10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.mp4 -
17.3 MB
10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.srt -
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11. Regression Analysis.html -
141 bytes
2. Regression Analysis - Common Metrics.mp4 -
12.6 MB
2. Regression Analysis - Common Metrics.srt -
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2. Regression Analysis - Common Metrics.vtt -
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3. [Hands On] - Linear Regression model using OLS.mp4 -
91.0 MB
3. [Hands On] - Linear Regression model using OLS.srt -
11.3 KB
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4. [Hands On] - Linear Regression - R Squared.mp4 -
10.3 MB
4. [Hands On] - Linear Regression - R Squared.srt -
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5. Gradient Descent.mp4 -
27.7 MB
5. Gradient Descent.srt -
10.0 KB
5. Gradient Descent.vtt -
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6. Linear Regression Online Gradient Descent.mp4 -
6.7 MB
6. Linear Regression Online Gradient Descent.srt -
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7. [Hands On] - Experiment Online Gradient.mp4 -
10.9 MB
7. [Hands On] - Experiment Online Gradient.srt -
4.4 KB
7. [Hands On] - Experiment Online Gradient.vtt -
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8. Decision Tree - What is Regression Tree.mp4 -
12.2 MB
8. Decision Tree - What is Regression Tree.srt -
6.1 KB
8. Decision Tree - What is Regression Tree.vtt -
5.5 KB
9. Decision Tree - What is Boosted Decision Tree Regression.mp4 -
4.3 MB
9. Decision Tree - What is Boosted Decision Tree Regression.srt -
2.0 KB
9. Decision Tree - What is Boosted Decision Tree Regression.vtt -
1.8 KB
1. What is Cluster Analysis.mp4 -
22.4 MB
1. What is Cluster Analysis.srt -
10.8 KB
1. What is Cluster Analysis.vtt -
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2. [Hands On] - Cluster Analysis Experiment 1.mp4 -
30.9 MB
2. [Hands On] - Cluster Analysis Experiment 1.srt -
13.2 KB
2. [Hands On] - Cluster Analysis Experiment 1.vtt -
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2.1 Callcenter Data.csv.csv -
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3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.mp4 -
18.4 MB
3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.srt -
7.3 KB
3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.vtt -
6.6 KB
4. Clustering or Cluster Analysis.html -
141 bytes
1. Section Introduction.mp4 -
5.4 MB
1. Section Introduction.srt -
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1. Section Introduction.vtt -
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10. Data Normalization - Scale and Reduce.mp4 -
5.3 MB
10. Data Normalization - Scale and Reduce.srt -
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11. [Hands On] - Data Normalization.mp4 -
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11. [Hands On] - Data Normalization.srt -
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12. PCA - What is PCA and Curse of Dimensionality.mp4 -
10.7 MB
12. PCA - What is PCA and Curse of Dimensionality.srt -
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12. PCA - What is PCA and Curse of Dimensionality.vtt -
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13. [Hands On] - Principal Component Analysis.mp4 -
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13. [Hands On] - Principal Component Analysis.srt -
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13. [Hands On] - Principal Component Analysis.vtt -
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14. Join Data - Join Multiple Datasets based on common keys.mp4 -
10.5 MB
14. Join Data - Join Multiple Datasets based on common keys.srt -
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14. Join Data - Join Multiple Datasets based on common keys.vtt -
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15. [Hands On] - Join Data - Experiment.mp4 -
15.1 MB
15. [Hands On] - Join Data - Experiment.srt -
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15. [Hands On] - Join Data - Experiment.vtt -
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15.1 EmpSalaryJC.csv.csv -
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15.2 EmpDeptJC.csv.csv -
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2. How to Summarize Data.mp4 -
11.7 MB
2. How to Summarize Data.srt -
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2. How to Summarize Data.vtt -
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3. [Hands On] - Summarize Data - Experiment.mp4 -
8.1 MB
3. [Hands On] - Summarize Data - Experiment.srt -
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4. Outliers Treatment - Clip Values.mp4 -
11.5 MB
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5. [Hands On] - Outliers Treatment - Clip Values.mp4 -
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5. [Hands On] - Outliers Treatment - Clip Values.srt -
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6. Clean Missing Data with MICE.mp4 -
13.1 MB
6. Clean Missing Data with MICE.srt -
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6. Clean Missing Data with MICE.vtt -
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7. [Hands On] - Clean Missing Data with MICE.mp4 -
15.9 MB
7. [Hands On] - Clean Missing Data with MICE.srt -
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7. [Hands On] - Clean Missing Data with MICE.vtt -
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7.1 MICE Loan Dataset.csv.csv -
37.1 KB
8. SMOTE - Create New Synthetic Observations.mp4 -
14.2 MB
8. SMOTE - Create New Synthetic Observations.srt -
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8. SMOTE - Create New Synthetic Observations.vtt -
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9. [Hands On] - SMOTE.mp4 -
15.5 MB
9. [Hands On] - SMOTE.srt -
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9. [Hands On] - SMOTE.vtt -
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9.1 LoanSMOTE.csv.csv -
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