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Listening Quiz: Cách Chúng Tôi Huấn Luyện Một Mô Hình Phân Loại Văn Bản – Easy Level
Th1 12, 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?
How a text classification model is trained
Why computers are faster than people
How to write a story for a class project
How to use labels in a spreadsheet
Explanation:
The speakers discuss what a text classification model is, how it learns from labeled examples, and how it is tested.
2.
According to Olivia, what are labels?
New kinds of text the model has never seen
Tags that tell the model what group the text belongs to
Scores used to measure how fast the model works
Special computers used to sort text
Explanation:
Olivia says labels are tags that tell the model what group the text belongs to.
3.
How does the computer learn to classify text?
By asking people to vote on each sentence
By reading one long article without labels
By using many examples of text with labels
By guessing the right group each time
Explanation:
Olivia explains that they give the model many examples of text with labels.
4.
Why does Olivia say the model is tested with new text it has not seen before?
To make the training examples easier to understand
To teach Robert how to write better labels
To check whether it can handle unfamiliar examples
To change the labels after training is finished
Explanation:
Testing with new text shows whether the model can correctly classify text it has not seen before.
5.
Why does Robert ask, “What do you mean by labels?”
He is trying to change the subject
He does not understand the term and wants a simple explanation
He wants Olivia to repeat the entire conversation
He already knows the answer and is joking
Explanation:
Robert asks for clarification because he does not understand what labels are.
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