Administrators can customize the Cloudera provided ML Runtimes to support Data Scientists’ specific use-cases. They can install additional OS packages, Python and R libraries, third-party drivers to enable connecting to external data stores, or even a new editor to be used. CML now enables registering these custom Runtimes and making them available for Data Scientists to use in their projects.
Data Scientists have specific requirements for their working environments, they require a set of R or Python libraries and ready-made connections to fetch from third-party data stores. With the new feature, administrators can create custom Runtimes that data scientists can use in CML.