Online Access Free Databricks-Machine-Learning-Professional Exam Questions

A machine learning engineer has developed a random forest model using scikit-learn, logged the model using MLflow as random_forest_model, and stored its run ID in the run_id Python variable.
They now want to deploy that model by performing batch inference on a Spark DataFrame spark_df. Which of the following code blocks can they use to create a function called predict that they can use to complete the task?

• A.
• B.
• C.
• D.It is not possible to deploy a scikit-learn model on a Spark DataFrame.
• E.

Which of the following Databricks-managed MLflow capabilities is a centralized model store?

• A.Model Serving
• B.Feature Store
• C.Models
• D.Experiments
• E.Model Registry

Which deployment paradigm can centrally compute predictions for a single record with exceedingly fast results?

• A.Edge/on-device
• B.Real-time
• C.None of these strategies will accomplish the task.
• D.Batch
• E.Streaming

A Machine Learning Engineer is working with a Spark DataFrame containing 100 million rows of retail transactions across thousands of stores. Each store requires its own demand forecasting model using the same scikit-learn pipeline. They want to train and apply these models in parallel for each store without collecting the data to the driver. Which approach will do this?

• A.Use groupBy("store_id").applyInPandas() to train and apply the model per group using a Pandas UDF.
• B.Convert the DataFrame to a Pandas DataFrame using .toPandas() and loop through each store locally.
• C.Use rdd.mapPartitions() to iterate through each store and apply the model logic in Python.
• D.Use pyspark.pandas to call .groupby("store_id").apply() and train the model on each group.

A machine learning engineer has developed a machine learning pipeline that produces a scikit- learn model model and computes the RMSE rmse. MAE mae, and R-squared r2 values for the test set. They now want to log these values with the MLflow run. These values are stored in the dictionary metrics.
They run the following code block:

The code block produces an error.
Which changes to the code block will successfully complete the task?

• A.Replace metrics with rmse, mae, r2
• B.Replace log_metric with log_metrics
• C.Replace mlflow.log_metric with mlflow.sklearn.log_metric
• D.Replace metrics with model