A data science team wants to use a Python package that is not included in the Databricks Runtime or Databricks Runtime for Machine Learning, but they are tired of installing the package at the top of each notebook. They plan on using this package in nearly every workload. They want to ensure that their solution works into the extended future.

Which of the following approaches can the data science team use to meet their requirements? Select one response.

Create a cluster$-$scoped init script and assign it to the cluster

Use the cluster libraries API to install it on the cluster

Create a cluster$-$named init script with the same name as their cluster

Use Databricks Container Services to install the package with Databricks Runtime for Machine Learning

Use the admin console to install the package to the clter