Free Databricks Machine Learning Associate Actual Exam Questions - Question 8 Discussion
Learning.
Which of the following steps will the data scientist need to perform outside of their AutoML
experiment?
Maybe D, since EDA is about understanding data before any modeling starts.
D/C? I agree deployment (C) is usually done outside AutoML, but EDA (D) also has to be separate since you need to understand and preprocess your data before feeding it in. AutoML handles tuning and evaluation, so those are inside, but you can’t skip proper exploration beforehand.
I think C fits best here. Databricks AutoML takes care of model tuning and evaluation during the experiment, but you generally have to deploy the model yourself afterward. EDA is definitely before AutoML, and tuning/evaluation happen inside it, so deployment stands out as the step done outside.
Maybe D. Exploratory data analysis usually happens before running AutoML, so it makes sense that you’d do it separately from the AutoML experiment.
Option C makes sense too. AutoML handles training, tuning, and evaluation automatically, but deploying the model typically requires separate steps outside of the AutoML workflow. So, after the AutoML experiment finishes, you usually need to take the chosen model and deploy it yourself.
It’s D, since EDA usually comes before AutoML runs.