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Exam Professional Machine Learning Engineer All Questions

View all questions & answers for the Professional Machine Learning Engineer exam

Exam Professional Machine Learning Engineer topic 1 question 203 discussion

Actual exam question from Google's Professional Machine Learning Engineer
Question #: 203
Topic #: 1
[All Professional Machine Learning Engineer Questions]

You work for a bank. You have been asked to develop an ML model that will support loan application decisions. You need to determine which Vertex AI services to include in the workflow. You want to track the model’s training parameters and the metrics per training epoch. You plan to compare the performance of each version of the model to determine the best model based on your chosen metrics. Which Vertex AI services should you use?

  • A. Vertex ML Metadata, Vertex AI Feature Store, and Vertex AI Vizier
  • B. Vertex AI Pipelines, Vertex AI Experiments, and Vertex AI Vizier
  • C. Vertex ML Metadata, Vertex AI Experiments, and Vertex AI TensorBoard
  • D. Vertex AI Pipelines, Vertex AI Feature Store, and Vertex AI TensorBoard
Show Suggested Answer Hide Answer
Suggested Answer: C 🗳️

Comments

Chosen Answer:
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dija123
5 months ago
Selected Answer: C
Agree with C
upvoted 1 times
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pinimichele01
7 months, 3 weeks ago
Selected Answer: C
agree with pikachu007
upvoted 1 times
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VipinSingla
8 months, 2 weeks ago
Why not B ?
upvoted 2 times
info_appsatori
3 months, 2 weeks ago
I guess because Vizier is a tool that helps to tune hyperparameters, and in a contrary Tensorboard is a tool to explore experiments.
upvoted 1 times
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Carlose2108
9 months ago
Selected Answer: C
I went C
upvoted 1 times
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winston9
10 months, 2 weeks ago
Selected Answer: C
use Tensorboard to track the model’s training parameters and the metrics per training epoch.
upvoted 2 times
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pikachu007
10 months, 2 weeks ago
Selected Answer: C
Vertex ML Metadata: Tracks model training parameters, hyperparameters, metrics, and lineage information. Stores metadata in a central repository for easy access and comparison. Integrates seamlessly with Vertex AI Experiments and TensorBoard. Vertex AI Experiments: Organizes and manages model training runs as experiments. Visualizes experiment results, including metrics and parameter comparisons. Facilitates tracking of the best performing model versions. Vertex AI TensorBoard: Provides detailed visualizations of training metrics and model performance. Enables analysis of model behavior at each training epoch. Integrates with Vertex AI Experiments for seamless access to experiment data.
upvoted 3 times
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Community vote distribution
A (35%)
C (25%)
B (20%)
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