Answer-first summary for fast verification
Answer: Develop a regression model using BigQuery ML.
The correct answer is B: Develop a regression model using BigQuery ML. BigQuery is a serverless, highly scalable data warehouse that can efficiently handle massive datasets, such as the tens of millions of records collected daily from your sensors. Using BigQuery ML allows you to leverage SQL syntax to create and train machine learning models directly within BigQuery, minimizing the development effort needed compared to custom models in TensorFlow, scikit-learn, or PyTorch. Additionally, BigQuery ML supports scheduling queries for automated model training, making it easy to set up daily training runs on the latest data with minimal manual intervention.
Author: LeetQuiz Editorial Team
Ultimate access to all questions.
No comments yet.
You are a data scientist at an industrial equipment manufacturing company. Your task is to develop a regression model to estimate the power consumption in the company’s manufacturing plants. The data comes from sensors that collect tens of millions of records daily across all the plants. You need to schedule daily training runs for your model, incorporating all data collected up to the current date. The solution should scale smoothly and require minimal development work. Given these requirements, what approach should you take?
A
Develop a custom TensorFlow regression model, and optimize it using Vertex AI Training.
B
Develop a regression model using BigQuery ML.
C
Develop a custom scikit-learn regression model, and optimize it using Vertex AI Training.
D
Develop a custom PyTorch regression model, and optimize it using Vertex AI Training.