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Google Exam Professional Machine Learning Engineer Topic 3 Question 93 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 93
Topic #: 3
[All Professional Machine Learning Engineer Questions]

You have recently developed a custom model for image classification by using a neural network. You need to automatically identify the values for learning rate, number of layers, and kernel size. To do this, you plan to run multiple jobs in parallel to identify the parameters that optimize performance. You want to minimize custom code development and infrastructure management. What should you do?

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Suggested Answer: D

by Luis at Nov 19, 2024, 12:38 AM

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Ernie
3 months ago
Wait, did someone say 'kernel size'? I'm picturing giant model kernels the size of basketballs. Now, that's what I call 'deep learning'!
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Celestina
1 months ago
D) Create a Vertex AI hyperparameter tuning job.
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Pilar
2 months ago
C) Create a custom training job that uses the Vertex AI Vizier SDK for parameter optimization.
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Sanjuana
2 months ago
B) Train an AutoML image classification model.
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William
2 months ago
A) Create a Vertex AI pipeline that runs different model training jobs in parallel.
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Shay
3 months ago
Hyperparameter tuning is where it's at! Just let the AI do its thing while I sit back and enjoy my coffee. Easy peasy!
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Isadora
2 months ago
Hyperparameter tuning is the way to go! Let the AI handle it while I relax.
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Jaime
2 months ago
D) Create a Vertex AI hyperparameter tuning job.
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Clay
2 months ago
B) Train an AutoML image classification model.
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Cecily
3 months ago
A) Create a Vertex AI pipeline that runs different model training jobs in parallel.
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Lucina
3 months ago
I prefer creating a custom training job using the Vertex AI Vizier SDK for parameter optimization. It gives us more control over the process.
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Galen
3 months ago
Haha, Vizier SDK for parameter optimization? Sounds like a one-way ticket to Complexity Town. I'll stick with the Vertex AI pipeline, thanks.
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Tandra
3 months ago
AuTandraL is tempting, but I want more control over my model. Gotta go with D - Vertex AI hyperparameter tuning for the win!
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Ciara
3 months ago
C) Create a custom training job that uses the Vertex AI Vizier SDK for parameter optimization.
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Sharika
3 months ago
A) Create a Vertex AI pipeline that runs different model training jobs in parallel.
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Rosann
3 months ago
D) Create a Vertex AI hyperparameter tuning job.
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Eleni
3 months ago
I agree with Kaitlyn, it will help us optimize performance without much custom code development.
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Kaitlyn
3 months ago
I think we should create a Vertex AI pipeline to run different model training jobs in parallel.
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Renay
3 months ago
Vertex AI pipeline sounds like the way to go! Minimal custom code and easy infrastructure management - sign me up!
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Graciela
2 months ago
D) Create a Vertex AI hyperparameter tuning job.
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Lawanda
2 months ago
C) Create a custom training job that uses the Vertex AI Vizier SDK for parameter optimization.
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Frankie
2 months ago
B) Train an AutoML image classification model.
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Candida
3 months ago
D) Create a Vertex AI hyperparameter tuning job.
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Carol
3 months ago
C) Create a custom training job that uses the Vertex AI Vizier SDK for parameter optimization.
upvoted 0 times
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Carlota
3 months ago
A) Create a Vertex AI pipeline that runs different model training jobs in parallel.
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Ronny
3 months ago
B) Train an AutoML image classification model.
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Elli
3 months ago
A) Create a Vertex AI pipeline that runs different model training jobs in parallel.
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