
Explanation:
Databricks Runtime ML clusters provide several benefits tailored for machine learning tasks:
Incorrect options clarified:
In summary, Databricks Runtime ML optimizes the machine learning workflow on Databricks by offering pre-configured clusters with essential libraries, thereby saving time and ensuring a smooth development process.
Ultimate access to all questions.
What advantages do Databricks Runtime ML clusters offer for machine learning workloads?
A
Databricks Runtime ML clusters are exclusively for CPU-enabled ML runtimes.
B
Databricks Runtime ML clusters include a wide range of popular machine learning libraries, such as TensorFlow, PyTorch, scikit-learn, and XGBoost.
C
Databricks Runtime ML clusters support only a minimal selection of machine learning libraries.
D
Databricks Runtime ML clusters enhance cluster creation speed and guarantee compatibility with the installed library versions.
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