Topic 1 Question 158
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?
Develop a custom TensorFlow regression model, and optimize it using Vertex AI Training.
Develop a regression model using BigQuery ML.
Develop a custom scikit-learn regression model, and optimize it using Vertex AI Training.
Develop a custom PyTorch regression model, and optimize it using Vertex AI Training.
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- 正解だと思う選択肢: B
Minimal development effort => BigQueryML
👍 2Mdso2023/07/31 - 正解だと思う選択肢: B
for scheduling daily training runs with minimal development work and seamless scaling, the best option is to develop a regression model using BigQuery ML (Option B). It allows you to perform model training and inference directly within BigQuery, taking advantage of its distributed processing capabilities to handle large datasets effortlessly.
👍 1PST212023/07/20
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