Deploy R Model as Web Service - 3 EASY Ways
Deploy R Model as Web Service - 3 EASY Ways.
In this video we're going to discover 3 easy ways on how to deploy machine learning model in production as REST APIs.
I'm regularly asked by my customers how they can deploy R code in production.
Or more precisely, how to deploy R models in production.
Here's what I cover:
00:00 | Intro
00:42 | Introduction to plumber
01:44 | Training the machine learning model
02:50 | Using plumber to create an API for the model
03:59 | Testing the plumber API
04:25 | Using Docker to host the plumber API
05:38 | Testing the deployed plumber API
06:28 | Using Machine Learning Server to host the model
09:07 | Introduction to the .NET Core app to test the APIs
10:23 | Testing the APIs with the .NET Core app
10:42 | Intro to SQL Server/Azure SQL Database ML Services
12:25 | Training the models and storing them in a SQL table
14:50 | Running predictions in the SQL Database
There are certainly more ways to deploy R model as API, but this should serve as a starting point.
If you know of any additional ways, please let me know in the comments.
I would like to publish another video about this topic.
For cloud computing, I use Microsoft Azure, but all the options I show here also run on-premises as well as with any other cloud provider.
If you wan't to have a look at the final code, please check out my GitHub repository:
https://github.com/SaschaDittmann/mac...
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🚀 Tools and services I use in this video:
R plumber:
https://www.rplumber.io/
Microsoft Machine Learning Server
https://www.microsoft.com/sql-server/...
Microsoft SQL Server R Services:
https://docs.microsoft.com/en-us/sql/...
Azure SQL Database Machine Learning Services with R:
https://docs.microsoft.com/en-us/azur...
R Studio:
https://rstudio.com/
Visual Studio Code:
https://code.visualstudio.com/
Azure Data Studio:
https://docs.microsoft.com/en-us/sql/...
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