[FreeTutorials.Us] Udemy - A-Z Machine Learning using Azure Machine Learning (AzureML)

Creation Time	Oct. 3, 2023, 12:27 a.m.
Last Access Time	Oct. 14, 2024, 5:14 p.m.
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Keywords	AzureML FreeTutorials - Us Udemy Machine A-Z Learning Azure using
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Total Files	317
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7. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.mp4 91.0 MB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.mp4 87.4 MB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.mp4 75.2 MB
1. Basics of Machine Learning/4. Why Machine Learning is the Future.mp4 68.7 MB
10. Feature Selection - Select a..highest impact/9. [Hands On] - Fisher Based LDA - Experiment.mp4 61.1 MB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.mp4 54.6 MB
4. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.mp4 52.2 MB
3. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.mp4 51.0 MB
13. Thank You and Bonus Lecture/1. Way Forward.mp4 50.0 MB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.mp4 50.0 MB
10. Feature Selection - Select a..highest impact/2. Pearson Correlation Coefficient.mp4 47.2 MB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.mp4 44.8 MB
3. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.mp4 38.9 MB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.mp4 36.2 MB
3. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.mp4 35.5 MB
4. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.mp4 35.1 MB
11. Recommendation System/1. What is a Recommendation System.mp4 35.0 MB
8. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.mp4 30.9 MB
4. Classification/1. Logistic Regression - What is Logistic Regression.mp4 30.7 MB
4. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.mp4 29.4 MB
7. Regression Analysis/5. Gradient Descent.mp4 27.7 MB
3. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.mp4 26.5 MB
4. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.mp4 25.2 MB
10. Feature Selection - Select a..highest impact/8. Fisher Based LDA - Intuition.mp4 24.1 MB
2. Getting Started with Azure ML/2. What is Azure ML and high level architecture..mp4 23.2 MB
8. Clustering/1. What is Cluster Analysis.mp4 22.4 MB
3. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.mp4 22.1 MB
5. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.mp4 21.9 MB
4. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.mp4 19.7 MB
4. Classification/3. Logistic Regression - Understand Parameters and Their Impact.mp4 19.5 MB
1. Basics of Machine Learning/3. Important Message About Udemy Reviews.mp4 19.2 MB
1. Basics of Machine Learning/1. What You Will Learn in This Section.mp4 19.2 MB
1. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.mp4 19.0 MB
4. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.mp4 18.6 MB
1. Basics of Machine Learning/5. What is Machine Learning.mp4 18.5 MB
8. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.mp4 18.4 MB
9. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.mp4 17.7 MB
11. Recommendation System/6. Understanding the Matchbox Recommendation Results.mp4 17.4 MB
7. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.mp4 17.3 MB
6. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.mp4 16.6 MB
9. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.mp4 15.9 MB
9. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.mp4 15.5 MB
9. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.mp4 15.1 MB
11. Recommendation System/2. Data Preparation using Recommender Split.mp4 14.9 MB
4. Classification/14. SVM - What is Support Vector Machine.mp4 14.9 MB
11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.mp4 14.6 MB
4. Classification/7. Decision Tree - What is Decision Tree.mp4 14.3 MB
9. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.mp4 14.2 MB
7. Regression Analysis/1. What is Linear Regression.mp4 14.0 MB
4. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.mp4 13.8 MB
4. Classification/5. Logistic Regression - Model Selection and Impact Analysis.mp4 13.8 MB
1. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.mp4 13.6 MB
2. Getting Started with Azure ML/1. What You Will Learn in This Section.mp4 13.6 MB
2. Getting Started with Azure ML/3. Creating a Free Azure ML Account.mp4 13.4 MB
1. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.mp4 13.3 MB
2. Getting Started with Azure ML/5. Azure ML Experiment Workflow.mp4 13.2 MB
10. Feature Selection - Select a..highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.mp4 13.2 MB
3. Data Processing/3. [Hands On] - Data Input-Output - Import Data.mp4 13.1 MB
9. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.mp4 13.1 MB
4. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.mp4 12.9 MB
7. Regression Analysis/2. Regression Analysis - Common Metrics.mp4 12.6 MB
7. Regression Analysis/8. Decision Tree - What is Regression Tree.mp4 12.2 MB
2. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.mp4 12.2 MB
4. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.mp4 12.1 MB
9. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.mp4 11.7 MB
9. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.mp4 11.5 MB
2. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.mp4 11.3 MB
11. Recommendation System/4. How to Score the Matchbox Recommender.mp4 10.9 MB
7. Regression Analysis/7. [Hands On] - Experiment Online Gradient.mp4 10.9 MB
9. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.mp4 10.7 MB
9. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.mp4 10.5 MB
7. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.mp4 10.3 MB
6. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.mp4 9.2 MB
10. Feature Selection - Select a..highest impact/3. Chi Square Test of Independence.mp4 8.3 MB
9. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.mp4 8.1 MB
10. Feature Selection - Select a..highest impact/1. Feature Selection - Section Introduction.mp4 7.7 MB
9. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.mp4 7.4 MB
7. Regression Analysis/6. Linear Regression Online Gradient Descent.mp4 6.7 MB
10. Feature Selection - Select a..highest impact/4. Kendall Correlation Coefficient.mp4 6.7 MB
10. Feature Selection - Select a..highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.mp4 6.4 MB
10. Feature Selection - Select a..highest impact/5. Spearman's Rank Correlation.mp4 6.4 MB
9. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.mp4 5.9 MB
4. Classification/11. Decision Forest - Parameters Explained.mp4 5.8 MB
6. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.mp4 5.6 MB
9. Data Processing - Solving Data Processing Challenges/1. Section Introduction.mp4 5.4 MB
9. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.mp4 5.3 MB
4. Classification/10.1 Bank Telemarketing.csv.csv 4.7 MB
7. Regression Analysis/9. Decision Tree - What is Boosted Decision Tree Regression.mp4 4.3 MB
1. Basics of Machine Learning/2.9 Section 04 - Classification - 002 - Decision Tree.pdf.pdf 3.4 MB
1. Basics of Machine Learning/2.11 Section 11 - Recommendation System.pdf.pdf 3.1 MB
1. Basics of Machine Learning/2.12 Section 10 - Feature Selection.pdf.pdf 2.9 MB
1. Basics of Machine Learning/2.14 Section 09 - Data Processing.pdf.pdf 2.8 MB
1. Basics of Machine Learning/2.5 Section 07 - Regression.pdf.pdf 2.8 MB
1. Basics of Machine Learning/2.4 Section 02 - Getting Started with AzureML.pdf.pdf 2.7 MB
2. Getting Started with Azure ML/6.1 ml_studio_overview_v1.1.pdf.pdf 2.2 MB
1. Basics of Machine Learning/2.3 Section - Text Analytics.pdf.pdf 2.0 MB
1. Basics of Machine Learning/2.1 Section 01 - Basics of Machine Learning.pdf.pdf 1.8 MB
1. Basics of Machine Learning/2.7 Section 08 - Clustering.pdf.pdf 1.5 MB
1. Basics of Machine Learning/2.6 Section 04 - Classification - 001 - Logistic Regression.pdf.pdf 1.4 MB
1. Basics of Machine Learning/2.10 Section 05 - Tune Hyperparameter.pdf.pdf 1.2 MB
1. Basics of Machine Learning/2.8 Section 04 - Classification - 003 - SVM.pdf.pdf 1.1 MB
1. Basics of Machine Learning/2.13 Section 03 - Data Pre-processing.pdf.pdf 1.0 MB
1. Basics of Machine Learning/2.2 Section 06 - Deploy Webservice.pdf.pdf 702.4 KB
2. Getting Started with Azure ML/6.2 microsoft-machine-learning-algorithm-cheat-sheet-v6.pdf.pdf 404.1 KB
13. Thank You and Bonus Lecture/1.1 Links for datasets.pdf.pdf 261.4 KB
10. Feature Selection - Select a..highest impact/9.1 Wine-Low-Medium-High.csv.csv 95.4 KB
3. Data Processing/5.1 Wine Quality Dataset.csv.csv 83.7 KB
4. Classification/6.1 winequality-red.csv.csv 83.7 KB
12. Text Analytics and Natural Language Processing/5.1 two-class complaints modified.txt.txt 47.4 KB
4. Classification/2.1 Loan Approval Prediction.csv.csv 37.1 KB
9. Data Processing - Solving Data Processing Challenges/7.1 MICE Loan Dataset.csv.csv 37.1 KB
4. Classification/4.1 004 - Logistic Regression - Understanding the results.xlsx.xlsx 24.0 KB
4. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.srt 21.9 KB
4. Classification/2. [Hands On] -Logistic Regression - Build Two-Class Loan Approval Prediction Model.vtt 19.8 KB
3. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.srt 18.0 KB
3. Data Processing/5. [Hands On] - Apply SQL Transformation, Clean Missing Data, Edit Metadata.vtt 16.2 KB
3. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.srt 16.1 KB
11. Recommendation System/1. What is a Recommendation System.srt 16.1 KB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.srt 15.2 KB
11. Recommendation System/1. What is a Recommendation System.vtt 14.6 KB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.srt 14.6 KB
3. Data Processing/6. [Hands On] - Sample and Split Data - Partition or Sample, Train and Test Data.vtt 14.5 KB
4. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.srt 13.9 KB
12. Text Analytics and Natural Language Processing/2. Text Pre-Processing.vtt 13.2 KB
8. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.srt 13.2 KB
4. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.srt 13.1 KB
12. Text Analytics and Natural Language Processing/4. Feature Hashing.vtt 12.7 KB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.srt 12.6 KB
4. Classification/12. [Hands On] - Two Class Decision Forest - Adult Census Income Prediction.vtt 12.5 KB
4. Classification/3. Logistic Regression - Understand Parameters and Their Impact.srt 12.5 KB
8. Clustering/2. [Hands On] - Cluster Analysis Experiment 1.vtt 11.9 KB
4. Classification/4. Understanding the Confusion Matrix, AUC, Accuracy, Precision, Recall and F1Score.vtt 11.9 KB
3. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.srt 11.5 KB
11. Recommendation System/5. [Hands On] - Restaurant Recommendation Experiment.vtt 11.3 KB
7. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.srt 11.3 KB
4. Classification/3. Logistic Regression - Understand Parameters and Their Impact.vtt 11.3 KB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.srt 11.0 KB
8. Clustering/1. What is Cluster Analysis.srt 10.8 KB
1. Basics of Machine Learning/5. What is Machine Learning.srt 10.7 KB
3. Data Processing/4. [Hands On] -Data Transform - Add RowsColumns, Remove Duplicates, Select Columns.vtt 10.3 KB
1. Basics of Machine Learning/4. Why Machine Learning is the Future.srt 10.1 KB
7. Regression Analysis/5. Gradient Descent.srt 10.0 KB
1. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.srt 10.0 KB
4. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.srt 9.9 KB
8. Clustering/1. What is Cluster Analysis.vtt 9.8 KB
1. Basics of Machine Learning/5. What is Machine Learning.vtt 9.7 KB
7. Regression Analysis/3. [Hands On] - Linear Regression model using OLS.vtt 9.7 KB
12. Text Analytics and Natural Language Processing/5. [Hands On] - Classify Customer Complaints using Text Analytics.vtt 9.6 KB
5. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.srt 9.6 KB
1. Basics of Machine Learning/4. Why Machine Learning is the Future.vtt 9.2 KB
1. Basics of Machine Learning/8. Types of Machine Learning Models - Classification, Regression, Clustering etc.vtt 9.2 KB
7. Regression Analysis/5. Gradient Descent.vtt 9.1 KB
3. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.srt 9.0 KB
4. Classification/10. [Hands On] Two-Class Boosted Decision Tree - Build Bank Telemarketing Prediction.vtt 9.0 KB
5. Hyperparameter Tuning/1. [Hands On] - Tune Hyperparameter for Best Parameter Selection.vtt 8.7 KB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.srt 8.6 KB
4. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.srt 8.4 KB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.srt 8.4 KB
1. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.srt 8.3 KB
3. Data Processing/2. [Hands On] - Data Input-Output - Convert and Unpack.vtt 8.1 KB
9. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.srt 8.0 KB
11. Recommendation System/2. Data Preparation using Recommender Split.srt 8.0 KB
11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.srt 8.0 KB
11. Recommendation System/6. Understanding the Matchbox Recommendation Results.srt 8.0 KB
3. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.srt 7.9 KB
1. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.srt 7.9 KB
4. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.srt 7.9 KB
10. Feature Selection - Select a..highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.srt 7.8 KB
4. Classification/7. Decision Tree - What is Decision Tree.srt 7.8 KB
12. Text Analytics and Natural Language Processing/3. Bag Of Words and N-Gram Models for Text features.vtt 7.6 KB
4. Classification/6. [Hands On] Logistic Regression - Build Multi-Class Wine Quality Prediction Model.vtt 7.5 KB
10. Feature Selection - Select a..highest impact/2. Pearson Correlation Coefficient.srt 7.5 KB
1. Basics of Machine Learning/7. Common Machine Learning Terms - Probability, Mean, Mode, Median, Range.vtt 7.5 KB
12. Text Analytics and Natural Language Processing/1. What is Text Analytics or Natural Language Processing.vtt 7.4 KB
2. Getting Started with Azure ML/5. Azure ML Experiment Workflow.srt 7.4 KB
8. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.srt 7.3 KB
11. Recommendation System/2. Data Preparation using Recommender Split.vtt 7.3 KB
4. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.srt 7.3 KB
9. Data Processing - Solving Data Processing Challenges/8. SMOTE - Create New Synthetic Observations.vtt 7.3 KB
11. Recommendation System/3. What is Matchbox Recommender and Train Matchbox Recommender.vtt 7.3 KB
11. Recommendation System/6. Understanding the Matchbox Recommendation Results.vtt 7.2 KB
9. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.srt 7.2 KB
3. Data Processing/1. [Hands On] - Data Input-Output - Upload Data.vtt 7.2 KB
1. Basics of Machine Learning/6. Understanding various aspects of data - Type, Variables, Category.vtt 7.1 KB
10. Feature Selection - Select a..highest impact/6. [Hands On] - Comparison Experiment for Correlation Coefficients.vtt 7.1 KB
4. Classification/13. [Hands On] - Decision Tree - Multi Class Decision Forest IRIS Data.vtt 7.0 KB
4. Classification/7. Decision Tree - What is Decision Tree.vtt 7.0 KB
13. Thank You and Bonus Lecture/2. Bonus Lecture.html 6.9 KB
10. Feature Selection - Select a..highest impact/1. Feature Selection - Section Introduction.srt 6.9 KB
9. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.srt 6.8 KB
9. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.srt 6.8 KB
6. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.srt 6.8 KB
2. Getting Started with Azure ML/5. Azure ML Experiment Workflow.vtt 6.7 KB
8. Clustering/3. [Hands On] - Cluster Analysis Experiment 2 - Score and Evaluate.vtt 6.6 KB
10. Feature Selection - Select a..highest impact/2. Pearson Correlation Coefficient.vtt 6.6 KB
4. Classification/8. Decision Tree - Ensemble Learning - Bagging and Boosting.vtt 6.6 KB
9. Data Processing - Solving Data Processing Challenges/5. [Hands On] - Outliers Treatment - Clip Values.vtt 6.5 KB
10. Feature Selection - Select a..highest impact/9. [Hands On] - Fisher Based LDA - Experiment.srt 6.5 KB
4. Classification/1. Logistic Regression - What is Logistic Regression.srt 6.4 KB
9. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.srt 6.4 KB
2. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.srt 6.4 KB
3. Data Processing/3. [Hands On] - Data Input-Output - Import Data.srt 6.4 KB
7. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.srt 6.3 KB
10. Feature Selection - Select a..highest impact/1. Feature Selection - Section Introduction.vtt 6.2 KB
9. Data Processing - Solving Data Processing Challenges/9.1 LoanSMOTE.csv.csv 6.2 KB
9. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.srt 6.2 KB
9. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.srt 6.2 KB
7. Regression Analysis/2. Regression Analysis - Common Metrics.srt 6.1 KB
9. Data Processing - Solving Data Processing Challenges/7. [Hands On] - Clean Missing Data with MICE.vtt 6.1 KB
9. Data Processing - Solving Data Processing Challenges/6. Clean Missing Data with MICE.vtt 6.1 KB
7. Regression Analysis/8. Decision Tree - What is Regression Tree.srt 6.1 KB
6. Deploy Webservice/3. [Hands On] - Use the Web Service - Example of Excel.vtt 6.1 KB
9. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.srt 6.0 KB
10. Feature Selection - Select a..highest impact/3. Chi Square Test of Independence.srt 6.0 KB
4. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.srt 5.9 KB
9. Data Processing - Solving Data Processing Challenges/4. Outliers Treatment - Clip Values.vtt 5.8 KB
2. Getting Started with Azure ML/6. Azure ML Cheat Sheet for Model Selection.vtt 5.8 KB
4. Classification/1. Logistic Regression - What is Logistic Regression.vtt 5.8 KB
10. Feature Selection - Select a..highest impact/9. [Hands On] - Fisher Based LDA - Experiment.vtt 5.8 KB
7. Regression Analysis/1. What is Linear Regression.srt 5.8 KB
3. Data Processing/3. [Hands On] - Data Input-Output - Import Data.vtt 5.7 KB
11. Recommendation System/4. How to Score the Matchbox Recommender.srt 5.7 KB
7. Regression Analysis/10. [Hands On] - Decision Tree - Experiment Boosted Decision Tree.vtt 5.7 KB
9. Data Processing - Solving Data Processing Challenges/2. How to Summarize Data.vtt 5.6 KB
4. Classification/5. Logistic Regression - Model Selection and Impact Analysis.srt 5.6 KB
7. Regression Analysis/2. Regression Analysis - Common Metrics.vtt 5.6 KB
9. Data Processing - Solving Data Processing Challenges/12. PCA - What is PCA and Curse of Dimensionality.vtt 5.5 KB
9. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.srt 5.5 KB
4. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.srt 5.5 KB
10. Feature Selection - Select a..highest impact/8. Fisher Based LDA - Intuition.srt 5.5 KB
7. Regression Analysis/8. Decision Tree - What is Regression Tree.vtt 5.5 KB
9. Data Processing - Solving Data Processing Challenges/14. Join Data - Join Multiple Datasets based on common keys.vtt 5.5 KB
10. Feature Selection - Select a..highest impact/3. Chi Square Test of Independence.vtt 5.4 KB
13. Thank You and Bonus Lecture/1. Way Forward.srt 5.4 KB
4. Classification/9. Decision Tree - Parameters - Two Class Boosted Decision Tree.vtt 5.4 KB
7. Regression Analysis/1. What is Linear Regression.vtt 5.3 KB
11. Recommendation System/4. How to Score the Matchbox Recommender.vtt 5.2 KB
4. Classification/5. Logistic Regression - Model Selection and Impact Analysis.vtt 5.0 KB
2. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.srt 5.0 KB
10. Feature Selection - Select a..highest impact/8. Fisher Based LDA - Intuition.vtt 5.0 KB
9. Data Processing - Solving Data Processing Challenges/9. [Hands On] - SMOTE.vtt 5.0 KB
4. Classification/15. [Hands On] - SVM - Adult Census Income Prediction.vtt 5.0 KB
13. Thank You and Bonus Lecture/1. Way Forward.vtt 4.9 KB
2. Getting Started with Azure ML/4. Azure ML Studio Overview and walk-through.vtt 4.5 KB
10. Feature Selection - Select a..highest impact/4. Kendall Correlation Coefficient.srt 4.4 KB
7. Regression Analysis/7. [Hands On] - Experiment Online Gradient.srt 4.4 KB
7. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.srt 4.2 KB
1. Basics of Machine Learning/3. Important Message About Udemy Reviews.srt 4.2 KB
10. Feature Selection - Select a..highest impact/4. Kendall Correlation Coefficient.vtt 4.0 KB
10. Feature Selection - Select a..highest impact/5. Spearman's Rank Correlation.srt 4.0 KB
7. Regression Analysis/7. [Hands On] - Experiment Online Gradient.vtt 3.9 KB
10. Feature Selection - Select a..highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.srt 3.9 KB
7. Regression Analysis/4. [Hands On] - Linear Regression - R Squared.vtt 3.8 KB
2. Getting Started with Azure ML/2. What is Azure ML and high level architecture..srt 3.8 KB
4. Classification/11. Decision Forest - Parameters Explained.srt 3.8 KB
1. Basics of Machine Learning/3. Important Message About Udemy Reviews.vtt 3.7 KB
4. Classification/14. SVM - What is Support Vector Machine.srt 3.7 KB
10. Feature Selection - Select a..highest impact/5. Spearman's Rank Correlation.vtt 3.6 KB
9. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.srt 3.6 KB
10. Feature Selection - Select a..highest impact/7. [Hands On] - Filter Based Selection - AzureML Experiment.vtt 3.5 KB
6. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.srt 3.5 KB
2. Getting Started with Azure ML/2. What is Azure ML and high level architecture..vtt 3.5 KB
4. Classification/11. Decision Forest - Parameters Explained.vtt 3.4 KB
4. Classification/14. SVM - What is Support Vector Machine.vtt 3.2 KB
9. Data Processing - Solving Data Processing Challenges/13. [Hands On] - Principal Component Analysis.vtt 3.2 KB
9. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.srt 3.1 KB
6. Deploy Webservice/2. [Hands On] - Deploy Machine Learning Model As a Web Service.vtt 3.1 KB
9. Data Processing - Solving Data Processing Challenges/1. Section Introduction.srt 3.1 KB
9. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.srt 2.9 KB
9. Data Processing - Solving Data Processing Challenges/3. [Hands On] - Summarize Data - Experiment.vtt 2.8 KB
9. Data Processing - Solving Data Processing Challenges/1. Section Introduction.vtt 2.8 KB
9. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.srt 2.8 KB
9. Data Processing - Solving Data Processing Challenges/10. Data Normalization - Scale and Reduce.vtt 2.7 KB
1. Basics of Machine Learning/1. What You Will Learn in This Section.srt 2.6 KB
6. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.srt 2.5 KB
9. Data Processing - Solving Data Processing Challenges/15. [Hands On] - Join Data - Experiment.vtt 2.4 KB
2. Getting Started with Azure ML/3. Creating a Free Azure ML Account.srt 2.4 KB
9. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.srt 2.4 KB
2. Getting Started with Azure ML/1. What You Will Learn in This Section.srt 2.3 KB
1. Basics of Machine Learning/1. What You Will Learn in This Section.vtt 2.3 KB
6. Deploy Webservice/1. Azure ML Webservice - Prepare the experiment for webservice.vtt 2.3 KB
2. Getting Started with Azure ML/3. Creating a Free Azure ML Account.vtt 2.2 KB
9. Data Processing - Solving Data Processing Challenges/11. [Hands On] - Data Normalization.vtt 2.2 KB
7. Regression Analysis/6. Linear Regression Online Gradient Descent.srt 2.2 KB
2. Getting Started with Azure ML/1. What You Will Learn in This Section.vtt 2.1 KB
7. Regression Analysis/9. Decision Tree - What is Boosted Decision Tree Regression.srt 2.0 KB
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3. Data Processing/1.1 Employee Dataset - Full.csv.csv 1.9 KB
3. Data Processing/4.1 Employee Dataset - TSV.txt.txt 1.9 KB
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3. Data Processing/4.2 Employee Dataset - AR2.csv.csv 1.3 KB
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0. Websites you may like/0. (1Hack.Us) Premium Tutorials-Guides-Articles & Community based Forum.url 377 bytes
1. Basics of Machine Learning/2. The course slides for all sections.html 336 bytes
0. Websites you may like/1. (FreeTutorials.Us) Download Udemy Paid Courses For Free.url 328 bytes
0. Websites you may like/2. (FreeCoursesOnline.Me) Download Udacity, Masterclass, Lynda, PHLearn, Pluralsight Free.url 286 bytes
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0. Websites you may like/4. (FTUApps.com) Download Cracked Developers Applications For Free.url 239 bytes
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3. Data Processing/3.1 Adult Dataset URL.txt.txt 74 bytes
4. Classification/13.1 IRIS Dataset Link.txt.txt 74 bytes

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