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 97 discussion

Actual exam question from Google's Professional Machine Learning Engineer

Question #: 97
Topic #: 1

[All Professional Machine Learning Engineer Questions]

You are a data scientist at an industrial equipment manufacturing company. You are developing a regression model to estimate the power consumption in the company’s manufacturing plants based on sensor data collected from all of the plants. The sensors collect tens of millions of records every day. You need to schedule daily training runs for your model that use all the data collected up to the current date. You want your model to scale smoothly and require minimal development work. What should you do?

A. Train a regression model using AutoML Tables.
B. Develop a custom TensorFlow regression model, and optimize it using Vertex AI Training.
C. Develop a custom scikit-learn regression model, and optimize it using Vertex AI Training.
D. Develop a regression model using BigQuery ML.

Show Suggested Answer

Suggested Answer: D 🗳️

by mil_spyro at Dec. 17, 2022, 11:12 a.m.

Comments

Submit Cancel

niketd

Highly Voted 2 years, 2 months ago

Selected Answer: D

The key is to understand the amount of data that needs to be used for training - the sensor collects tens of millions of records every day and the model needs to use all the data up to the current date. There is a limitation for AutoML is 100M rows -> https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/prepare-data

upvoted 16 times

...

Laur_C

Most Recent 6 months, 1 week ago

Selected Answer: A

Old question - quota for AutoML (now Vertex AI) is Between 1,000 and 200,000,000 rows so should be able to handle well. Plus "minimal development work" is usually a key word for AutoML (Vertex Ai)

upvoted 3 times

Laur_C

6 months, 1 week ago

AutoML modal limits: https://cloud.google.com/vertex-ai/docs/quotas#tabular_1

upvoted 2 times

...

pinimichele01

1 year, 1 month ago

Selected Answer: D

There is a limitation for AutoML is 100M rows -> https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/prepare-data

upvoted 1 times

...

vale_76_na_xxx

1 year, 6 months ago

I go for A

upvoted 2 times

pinimichele01

1 year, 1 month ago

There is a limitation for AutoML is 100M rows -> https://cloud.google.com/vertex-ai/docs/tabular-data/classification-regression/prepare-data

upvoted 1 times

...

Mickey321

1 year, 7 months ago

Selected Answer: A

Either A or D . Since not stated where is sensor data stored . hence go for A

upvoted 2 times

...

PST21

1 year, 11 months ago

Ans D. BigQuery ML allows you to schedule daily training runs by incorporating the latest data collected up to the current date. By specifying the appropriate SQL query, you can include all the relevant data in the training process, ensuring that your model is updated regularly.

upvoted 2 times

maukaba

1 year, 7 months ago

it says "use all the data collected up to the current date" not a just a selection of "relevant" (?!) data

upvoted 1 times

...

ggwp1999

2 years, 1 month ago

Selected Answer: A

I would go with A because it states that it requires minimal development work. Not sure tho, correct me if I’m wrong

upvoted 3 times

...

M25

2 years, 1 month ago

Selected Answer: D

Went with D

upvoted 1 times

...

JamesDoe

2 years, 2 months ago

Selected Answer: A

Old question, the quotas were removed when they moved AutoML into VertexAI. https://cloud.google.com/vertex-ai/docs/quotas#model_quotas#tabular

upvoted 3 times

...

Yajnas_arpohc

2 years, 3 months ago

Would go w A given the specifics mentioned in question. BigQuery is an unnecessary distraction IMO (e.g. why would we assume BigQuery and not BigTable!)

upvoted 1 times

...

TNT87

2 years, 3 months ago

Selected Answer: D

Answer D https://cloud.google.com/blog/products/data-analytics/automl-tables-now-generally-available-bigquery-ml This legacy version of AutoML Tables is deprecated and will no longer be available on Google Cloud after January 23, 2024. All the functionality of legacy AutoML Tables and new features are available on the Vertex AI platform. See Migrate to Vertex AI to learn how to migrate your resources.

upvoted 2 times

...

FherRO

2 years, 3 months ago

Selected Answer: A

You require minimal development work and the question doesn't mention if your data is stored in BQ

upvoted 1 times

...

Ade_jr

2 years, 5 months ago

Selected Answer: D

Answer is D, AutoML has 200M rows as limits

upvoted 3 times

...

ares81

2 years, 5 months ago

Selected Answer: A

A and D seem both good, but A works better, for me.

upvoted 1 times

...

mymy9418

2 years, 5 months ago

Selected Answer: A

But BQML also has limits on training data https://cloud.google.com/bigquery-ml/quotas

upvoted 2 times

...

hiromi

2 years, 5 months ago

Selected Answer: D

Vote for D A dosen't work because AutoML has limits on training data - https://www.examtopics.com/exams/google/professional-machine-learning-engineer/view/10/

upvoted 3 times

behzadsw

2 years, 5 months ago

Wrong. The limit is 200 M records. We have 10M records. see: https://cloud.google.com/automl-tables/docs/quotas

upvoted 1 times

adarifian

2 years, 2 months ago

it's more than 10M. the training needs to use all the data collected up to the current date

upvoted 2 times

...

mil_spyro

2 years, 6 months ago

Selected Answer: D

BigQuery ML can scale smoothly and requires minimal development work. Model can be build using SQL queries rather than writing custom code.

upvoted 3 times

...