Databricks Certified Machine Learning Associate Exam
Last Update Dec 12, 2024
Total Questions : 74 With Methodical Explanation
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Last Update Dec 12, 2024
Total Questions : 74
Last Update Dec 12, 2024
Total Questions : 74
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Which of the following hyperparameter optimization methods automatically makes informed selections of hyperparameter values based on previous trials for each iterative model evaluation?
A data scientist is performing hyperparameter tuning using an iterative optimization algorithm. Each evaluation of unique hyperparameter values is being trained on a single compute node. They are performing eight total evaluations across eight total compute nodes. While the accuracy of the model does vary over the eight evaluations, they notice there is no trend of improvement in the accuracy. The data scientist believes this is due to the parallelization of the tuning process.
Which change could the data scientist make to improve their model accuracy over the course of their tuning process?
A machine learning engineer wants to parallelize the training of group-specific models using the Pandas Function API. They have developed thetrain_modelfunction, and they want to apply it to each group of DataFramedf.
They have written the following incomplete code block:
Which of the following pieces of code can be used to fill in the above blank to complete the task?