Big companies that started earlier with ML, started with R, as it was not until 2017 that python surpassed R as the preferred language for ML. Still many companies have models running in batch on Spark clusters and those models are implemented in R.
In CP4D we have a partial support for R, loosing the opportunity to provide support to the full life cycle of models.
|Who would benefit from this IDEA?||R practitioners, which use to be the senior datascientists in many large companies, target of IBM|
How should it work?
In Watson Studio we support R (RStudio) and in CP4D 3.0 we are supporting R Shiny applications, which can be deployed in WML deployment spaces. But those are kind of web based applications, with presentation layer. Some customers are deploying R models as web services using Plumber (https://www.rplumber.io/), which allows to "apify" the R model and deploy it as a docker container.
If WML supported the R model "apification" and hosting of the api, it would also provide a better support opportunity for Openscale to support R models monitoring. And most important, we would provide an end to end dupport to R model life cyle.
|Priority Justification||Customers with installed base of R models are now taking decisions related to their data platform modernization.|
|Client Name||Ask me.|
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