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Data Science with Microsoft Azure and R

Video Description

In this Data Science with Microsoft Azure and R training course, expert author Stephen Elston will teach you how to develop and deploy effective machine learning models in the Microsoft Azure Machine Learning (ML) environment. This course is designed for users that are familiar with R.

You will start with an overview of Azure ML, then move into an introduction to R in Azure ML. From there, Stephen will teach you about data munging and SQL in Azure ML, as well as how to use the dplyr package, install R packages in Azure ML, and reshape data with tidyr. This video tutorial also covers feature selection and dimensionality reduction, functional programming with R, and R object communications. Finally, you will learn about Azure ML web services, including how to create and update an Azure ML web service.

Once you have completed this computer based training course, you will be fully capable of developing and deploying your own ML models in the Microsoft Azure ML environment.

Table of Contents

  1. Introduction
    1. Introduction 00:05:29
    2. About The Author 00:01:15
  2. Overview Of Azure ML
    1. Introduction To Azure ML Studio 00:00:54
    2. Experiments And Workflows In Azure ML Studio 00:05:52
    3. Azure ML Modules 00:03:53
    4. Data I/O In Azure ML 00:05:34
    5. Creating And Evaluating A First Machine Learning Model 00:06:33
    6. Documentation And Examples 00:03:41
  3. Introduction To R In Azure ML
    1. Editing, Debugging And Executing R In Azure ML 00:03:59
    2. An Execute R Script Example 00:13:28
    3. The Create R Model Module 00:09:34
  4. Data Science Examples
    1. Overview Of Data Science Examples 00:09:11
    2. The Data Science Process 00:07:28
  5. Data Munging In Azure ML
    1. Introduction To Data Transformation And Cleaning 00:01:53
    2. Dealing With Metadata 00:05:08
    3. Duplicate And Missing Data 00:06:00
    4. Standardization And Transformation 00:04:57
    5. Errors And Outliers 00:04:18
    6. Quantization And Categories 00:06:40
    7. Combining Data Joins 00:05:04
  6. SQL In Azure ML
    1. Introduction To Apply SQL Transformation Module 00:03:59
    2. Apply SQL Transformation Exercise 00:03:17
  7. Using The dplyr Package
    1. Intro To dplyr 00:07:41
    2. dplyr Example - Part 1 00:02:14
    3. dplyr Example - Part 2 00:03:18
  8. Installing R Packages In Azure ML
    1. Installing R Packages 00:04:17
  9. Reshaping Data With tidyr
    1. Reshaping Data With tidyr 00:07:24
  10. Time Series Data In Azure ML
    1. Date-Time Classes In Azure ML 00:06:16
    2. POSIXct Example 00:03:50
  11. The ggplot2 Package
    1. Intro To ggplot2 00:04:24
    2. ggplot2 Exercise 00:04:01
  12. Feature Selection And Dimensionality Reduction
    1. Introduction To Feature Selection And Dimensionality Reduction 00:08:53
    2. Exercise - Filter Based Feature Selection 00:03:41
    3. Exercise - randomForest Feature Selection 00:06:10
    4. Projection Methods for Dimensionality Reduction 00:12:21
  13. Functional Programming With R
    1. Introduction To Functional Programming With R 00:08:45
    2. Functional Programming Example 00:05:25
  14. Regression Example
    1. Introduction To Regression Example 00:05:20
    2. Data Preparation Example 00:08:52
    3. Examining Correlations 00:06:12
    4. Time Series Plots 00:06:11
    5. Understanding Features With Box Plots 00:07:01
    6. Other Exploratory Plots 00:05:45
    7. Feature Selection - Regression 00:05:02
    8. Model Evaluation With Time Series Plots 00:10:14
    9. Model Evaluation Of Residuals - Part 1 00:04:30
    10. Model Evaluation Of Residuals - Part 2 00:05:03
  15. Regression Example - Improving the Model
    1. Introduction To Improving the Model 00:01:08
    2. Using An R Model 00:05:59
    3. Creating A New Azure ML Model 00:03:36
    4. Trimming Outliers 00:10:53
    5. Optimizing Model Parameters 00:07:44
    6. Further Improvements And Summary 00:03:43
  16. R Object Communications In Azure ML
    1. Introduction To R Object Serialization 00:04:22
    2. R Object Serialization Example 00:05:18
  17. Classification Example
    1. Introduction To Classification Example 00:04:37
    2. Data Preparation - Part 1 00:03:01
    3. Data Preparation - Part 2 00:07:42
    4. Exploring The Data 00:08:01
    5. Balance Cases 00:03:26
    6. Feature Selection 00:06:03
    7. Building Initial Models 00:05:45
    8. Model Evaluation 00:09:12
    9. First R Model 00:05:01
    10. Improving the R Model 00:06:31
    11. Summary 00:03:38
  18. Azure ML Web Services
    1. Overview Of Publishing Azure ML Models As Web Services 00:03:48
    2. Creating An Azure ML Web Service 00:10:27
    3. Updating An Azure ML Web Service 00:02:49
    4. R Model Publishing 00:08:36
    5. Summary 00:04:09
  19. Conclusion
    1. Wrap-Up 00:02:48