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Amazon MLS-C01 Exam - Topic 2 Question 27 Discussion

A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hoursWith the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s)Which visualization will accomplish this?
D) A scatter plot showing the correlation between maximum tree depth and the objective metric.
A) A histogram showing whether the most important input feature is Gaussian.
B) A scatter plot with points colored by target variable that uses (-Distributed Stochastic Neighbor Embedding (I-SNE) to visualize the large number of input variables in an easier-to-read dimension.
C) A scatter plot showing (he performance of the objective metric over each training iteration

Amazon MLS-C01 Exam - Topic 2 Question 27 Discussion

Actual exam question for Amazon's MLS-C01 exam
Question #: 27
Topic #: 2
[All MLS-C01 Questions]

A Machine Learning Specialist kicks off a hyperparameter tuning job for a tree-based ensemble model using Amazon SageMaker with Area Under the ROC Curve (AUC) as the objective metric This workflow will eventually be deployed in a pipeline that retrains and tunes hyperparameters each night to model click-through on data that goes stale every 24 hours

With the goal of decreasing the amount of time it takes to train these models, and ultimately to decrease costs, the Specialist wants to reconfigure the input hyperparameter range(s)

Which visualization will accomplish this?

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Suggested Answer: D

by Annabelle at May 06, 2022, 01:24 AM

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Marisha
9 months ago
Does tuning hyperparameters really save that much time?
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Chauncey
9 months ago
Wait, I didn’t know models could retrain every night!
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Jarod
9 months ago
Not sure if a histogram is really useful here.
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Nadine
9 months ago
I think option C is the best for tuning hyperparameters.
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Stephen
10 months ago
AUC is a solid choice for the objective metric!
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Antonio
10 months ago
I'm a little confused by the options here. None of them seem to directly address the specific task of verifying the "Save" input method and returning the autogenerated draft ID. I'll need to think this through carefully and make sure I understand the correct approach.
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Lyndia
10 months ago
I've got a strategy for this. I'll start by considering the key characteristics of each storage/use type, then see which one best fits the scenario described in the question. Gotta use that process of elimination!
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Jolene
10 months ago
Hmm, this looks like a tricky one. I'll need to think carefully about the data flow programming paradigm and how each of these options relates to it.
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