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You are tasked with setting up a new Databricks environment for a machine learning project. Your team requires a cluster that can handle the computational demands of training large-scale models. How would you go about creating a cluster with the Databricks Runtime for Machine Learning and ensuring that a specific Python library is available to all notebooks?
Explanation:
Option B is the correct approach as it leverages the Databricks Runtime for Machine Learning, which is optimized for machine learning workloads. Additionally, using the Databricks library management system ensures that the library is available to all notebooks without manual installation in each one.