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Listening Quiz: Giải Thích Về Sự Trôi Dạt Hiệu Suất Mô Hình Và Việc Huấn Luyện Lại – Easy Level
Th9 10, 2025
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bởi
Anna Phạm
trong
Tiếng Anh dành cho Nhà khoa học dữ liệu (English for Data Scientist)
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1.
What is the conversation mainly about?
Why a computer system cannot be monitored
Ways to collect more training data for a project
How to build a new machine learning model from scratch
A drop in model accuracy and how to address it
Explanation:
Olivia explains that the model’s accuracy has dropped, identifies this as performance drift, and says retraining and monitoring are needed to fix it.
2.
What does Olivia suggest for retraining the model?
Once a year
Every three months
Only after the model fails completely
Every week
Explanation:
Olivia says, “I suggest every three months for now.”
3.
What can cause performance drift, according to Olivia?
A lack of internet access
A change in data or new patterns
Too many meetings between staff members
A broken computer screen
Explanation:
Olivia says that data changes or new patterns can cause performance drift.
4.
Why does Olivia say continuous monitoring is important?
To replace retraining completely
To provide early alerts about problems
To stop the model from learning new data
To make retraining unnecessary
Explanation:
Olivia says continuous monitoring is important for early alerts, which implies it helps catch problems sooner.
5.
Why does Mark ask whether retraining will improve the model’s accuracy?
He is asking whether the model should be deleted
He wants to know if the model can be used without data
He is asking how to change the conversation topic
He wants to confirm that retraining can help fix the performance drift
Explanation:
Mark has just asked how to fix the drift, so his question about retraining is to confirm whether it will help improve accuracy.
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