A machine learning team is working on a project that requires a specific version of the numpy library. They aim to ensure this version is used across all notebooks in their Databricks workspace. What is the best approach to achieve this?

Real Exam

Run %pip install numpy== once on any notebook attached to the cluster.

10.5%

Edit the cluster to use the Databricks Runtime for Machine Learning.

21.1%

Add numpy== to the cluster's library dependencies.

57.9%

Set the PYTHON_VERSION variable in the cluster configuration to the required version._

10.5%

There is no way to enforce a specific version of numpy on a cluster.

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