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Free Databricks-Machine-Learning-Associate Exam Questions - Databricks Databricks-Machine-Learning-Associate Exam

Databricks Databricks-Machine-Learning-Associate Exam

Databricks-Machine-Learning-Associate Exam - Prepare from Latest, Not Redundant Questions!

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Databricks Databricks-Machine-Learning-Associate Exam Sample Questions:

Q1.

A machine learning engineer is trying to scale a machine learning pipeline by distributing its single-node model tuning process. After broadcasting the entire training data onto each core, each core in the cluster can train one model at a time. Because the tuning process is still running slowly, the engineer wants to increase the level of parallelism from 4 cores to 8 cores to speed up the tuning process. Unfortunately, the total memory in the cluster cannot be increased.

In which of the following scenarios will increasing the level of parallelism from 4 to 8 speed up the tuning process?

Q2.

A machine learning engineer wants to parallelize the inference of group-specific models using the Pandas Function API. They have developed the apply_model function that will look up and load the correct model for each group, and they want to apply it to each group of DataFrame df.

They have written the following incomplete code block:

q2_Databricks-Machine-Learning-Associate

Which piece of code can be used to fill in the above blank to complete the task?

Q3.

A data scientist has been given an incomplete notebook from the data engineering team. The notebook uses a Spark DataFrame spark_df on which the data scientist needs to perform further feature engineering. Unfortunately, the data scientist has not yet learned the PySpark DataFrame API.

Which of the following blocks of code can the data scientist run to be able to use the pandas API on Spark?

Q4.

A data scientist is using the following code block to tune hyperparameters for a machine learning model:

q4_Databricks-Machine-Learning-Associate

Which change can they make the above code block to improve the likelihood of a more accurate model?

Q5.

Which of the following describes the relationship between native Spark DataFrames and pandas API on Spark DataFrames?

Solutions:
Question: 1 Answer: B
Question: 2 Answer: A
Question: 3 Answer: A
Question: 4 Answer: A
Question: 5 Answer: C
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