Train and deploy ML models with R and plumber on Vertex AI

R is one of the most widely used programming languages for statistical computing and machine learning. Many data scientists love it, especially for the rich world of packages from tidyverse, an opinionated collection of R packages for data science. Besides the tidyverse, there are over 18,000 open-source packages on CRAN, the package repository for R. RStudio, available as desktop version or on the Google Cloud Marketplace, is a popular Integrated Development Environment (IDE) used by data professionals for visualization and machine learning model development. Once a model has been built successfully, a recurring question among data scientists is: "How do I deploy models written in the R language to production in a scalable, reliable and low-maintenance way?" In this blog post, you will walk through how to use Google Vertex AI to train and deploy enterprise-grade machine learning models built with R. Managing machine learning models on Vertex AI can be done in a variety of ways, including using the User Interface of the Google Cloud Console, API calls, or the Vertex AI SDK for Python.