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PROFESSIONAL-MACHINE-LEARNING-ENGINEER · Question #108
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…
The correct answer is D. Develop a regression model using BigQuery ML. 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 There is a limitation for AutoML is 100M rows ->…
Submitted by tunde_lagos· Apr 18, 2026ML model development
Question
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?
Options
- ATrain a regression model using AutoML Tables.
- BDevelop a custom TensorFlow regression model, and optimize it using Vertex AI Training.
- CDevelop a custom scikit-learn regression model, and optimize it using Vertex AI Training.
- DDevelop a regression model using BigQuery ML.
How the community answered
(45 responses)- A9% (4)
- B2% (1)
- C18% (8)
- D71% (32)
Explanation
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 There is a limitation for AutoML is 100M rows -> https://cloud.google.com/vertex-ai/docs/tabular- data/classification-regression/prepare-data
Topics
#BigQuery ML#Scalable machine learning#Managed services#Regression models
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