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Databricks Exam Databricks Machine Learning Professional Topic 12 Question 30 Discussion

Actual exam question for Databricks's Databricks Machine Learning Professional exam
Question #: 30
Topic #: 12
[All Databricks Machine Learning Professional Questions]

A machine learning engineer is converting a Hyperopt-based hyperparameter tuning process from manual MLflow logging to MLflow Autologging. They are trying to determine how to manage nested Hyperopt runs with MLflow Autologging.

Which of the following approaches will create a single parent run for the process and a child run for each unique combination of hyperparameter values when using Hyperopt and MLflow Autologging?

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Suggested Answer: C

Contribute your Thoughts:

Georgene
2 days ago
I think E sounds too good to be true.
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Clorinda
8 days ago
A is definitely the way to go for nested runs!
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Quentin
13 days ago
I’m pretty sure there’s a way to manage nested runs, but I’m leaning towards the idea that there might be limitations with Autologging and Hyperopt.
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Julianna
19 days ago
I feel like starting a manual child run within the objective function might be the right move, but I need to double-check how that interacts with Autologging.
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Jannette
24 days ago
I think I read somewhere that MLflow Autologging can handle nested runs automatically, but I can't recall the specifics.
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Harley
1 month ago
I remember that starting a manual parent run is a common approach in similar practice questions, but I'm not entirely sure if it's the best option here.
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Stephaine
1 month ago
I think option A is the way to go here. Starting a manual parent run before calling fmin in the Hyperopt process seems like the most straightforward approach to get the desired nested run structure. The other options don't seem to directly address the requirement of having a single parent run and child runs for each hyperparameter combination.
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Virgilio
1 month ago
I'm not sure about this one. The question is asking about a specific approach, but I'm not confident that any of the options provided are the correct solution. I might need to do some additional research or experimentation to determine the best way to handle this scenario with MLflow Autologging and Hyperopt.
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Jennifer
1 month ago
Okay, I think I've got this figured out. Based on the options provided, the right approach is to start a manual parent run before calling fmin in the Hyperopt process. That way, MLflow Autologging can automatically create the child runs for each unique hyperparameter combination. The other options don't seem to address the nested run requirement.
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Izetta
1 month ago
Hmm, this is a tricky one. I'm not too familiar with the details of how MLflow Autologging works, so I'm a bit confused about the best way to approach this. I'll need to review the MLflow documentation to see if there are any specific guidelines for using it with Hyperopt.
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Agustin
1 month ago
I think the key here is to understand how MLflow Autologging interacts with the Hyperopt process. The question is asking about managing nested runs, so I'm guessing the right approach involves starting a parent run and then letting the child runs happen automatically within the Hyperopt objective function.
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Delfina
7 months ago
Ah, the joys of machine learning engineering – where the only constant is the constant need to find creative solutions to complex problems. At least it keeps things interesting, right?
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Tamekia
6 months ago
C: A) Startinq a manual parent run before calling fmin
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Alexia
6 months ago
B: E) MLflow Autoloqqinq will automatically accomplish this task with Hyperopt
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Milly
6 months ago
A: C) Starting a manual child run within the objective function
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Hillary
7 months ago
I'm feeling a bit like a hyperparameter myself, trying to figure out the best way to log these nested Hyperopt runs. Maybe I should just let the computer sort it out and go grab a cup of coffee.
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Maybelle
7 months ago
Option B seems like a good compromise. Using a built-in model flavor should make the logging process a bit more straightforward. As long as it plays nicely with Hyperopt, I think that could be the way to go.
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Wai
6 months ago
I agree, it sounds like a practical solution. It's important to streamline the process for nested runs with Hyperopt and MLflow Autologging.
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Adelaide
6 months ago
Option B seems like a good compromise. Using a built-in model flavor should make the logging process a bit more straightforward. As long as it plays nicely with Hyperopt, I think that could be the way to go.
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Alexis
7 months ago
Option D is a bit of a bummer, but I'm not surprised. Nested runs can be a tricky thing to manage, even with powerful tools like Hyperopt and MLflow. Guess I'll have to get creative with my approach.
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Edison
7 months ago
I think Option C might be the way to go. Starting a manual child run within the objective function sounds like it would give me the level of control I need to manage the nested structure. Worth a try!
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Lynelle
5 months ago
Let me know how it goes with implementing Option C!
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Jettie
5 months ago
It's worth a try to see if it gives you the control you need.
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Sophia
6 months ago
I agree, starting a manual child run within the objective function seems like a good approach.
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Joanne
6 months ago
Option C might work well for managing nested runs.
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Nenita
7 months ago
Option E sounds promising, but I'm not sure if MLflow Autologging can really handle the complexity of nested Hyperopt runs. I'd feel more comfortable with a manual approach to ensure I have full control over the logging.
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Cherelle
7 months ago
But wouldn't starting a manual child run within the objective function be more efficient?
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Johna
7 months ago
I disagree, I believe option E is the correct choice.
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Cherelle
7 months ago
I think option C is the way to go.
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