In this section, we will illustrate the process of bringing your own Docker container to Amazon SageMaker. Particularly, we will focus on training and hosting R models seamlessly in Amazon SageMaker. Rather than reinventing the wheel in terms of building ML models using SageMaker's built-in algorithms, data scientists and machine learning engineers can reuse the work that they've done in R in SageMaker.
The following is the architecture regarding how different AWS components interact to train and host R models:
To follow the preceding architectural diagram, we start with Amazon Elastic Container Registry (ECR):
- We create a Docker image containing an underlying operating system, prerequisites to train a recommender algorithm in R, and R code for training and scoring the User-Based Collaborative Filtering (UBCF) recommender algorithm...
