The implementation of linear regression in Spark ML first attempts to solve the linear regression problem using matrix decomposition, but this method does not scale well to large datasets with a large number of variables.Which of the following approaches does Spark ML use to distribute the training of a linear regression model for large data?
Which of the following describes the relationship between native Spark DataFrames and pandas API on Spark DataFrames?
A data scientist is using MLflow to track their machine learning experiment. As a part of each of their MLflow runs, they are performing hyperparameter tuning. The data scientist would like to have one parent run for the tuning process with a child run for each unique combination of hyperparameter values. All parent and child runs are being manually started with mlflow.start_run.Which of the following approaches can the data scientist use to accomplish this MLflow run organization?
Which of the following approaches can be used to view the notebook that was run to create an MLflow run?
A data scientist is developing a machine learning pipeline using AutoML on Databricks Machine Learning.Which of the following steps will the data scientist need to perform outside of their AutoML experiment?
A machine learning engineering team has a Job with three successive tasks. Each task runs a single notebook. The team has been alerted that the Job has failed in its latest run.Which of the following approaches can the team use to identify which task is the cause of the failure?
