SQL Server Machine Learning Services: R

SQL Server Machine Learning Services: R

English | MP4 | AVC 1280×720 | AAC 48KHz 2ch | 2h 11m | 269 MB

SQL Server now includes support for direct execution of R code. This integration allows complex data science analyses to be performed quickly in a secure environment, without having to export data sets first. In this course, database expert Adam Wilbert walks through the steps of enabling the required components—including Machine Learning Services for R—and writing basic R scripts. He also shows how to retrieve and work with data stored in SQL Server tables, create data visualizations with external R libraries, and package scripts as stored procedures. At the end of the course, traditional SQL Server users will be able to dive deeper into using R and traditional R developers will be able to take advantage of using SQL Server as the source of data to create higher-performing analyses.

Topics include:

  • Installing Machine Learning Services
  • Writing your first R script
  • Importing data
  • Querying data
  • Outputting data to a result set
  • Creating a data frame
  • Creating SQL stored procedures from R scripts
  • Producing graphs, plots, and charts
  • Creating an external data science client
Table of Contents

1 Analyze SQL Server data with R
2 What you should know
3 Make the most of the exercise files
4 What is Machine Learning Services (MLS)
5 Install Machine Learning Services for R
6 Enable script execution in SQL Server
7 Write your first R script
8 R data types
9 Variables in R
10 Import a data set from SQL Server
11 Query data into an R data frame
12 Output data to a result set
13 Select values from a data frame
14 Create a data frame from vectors
15 Subset a data frame
16 Challenge Import data
17 Solution Import data
18 Sample a data set
19 Parameterize a stored procedure
20 Challenge Write a stored procedure
21 Solution Write a stored procedure
22 View installed packages
23 Produce graphs and plots
24 Create a bar plot
25 Challenge Create a pie chart
26 Solution Create a pie chart
27 Install MLS on a standalone server
28 Add development tools to a client
29 Install and configure RStudio
30 Next steps