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Listening Quiz: Học Máy cho Phân Loại Vật Lý Hạt – Advanced Level
Th10 12, 2025
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bởi
Anna Phạm
trong
Tiếng Anh dành cho Nhà vật lý học (English for Physicist)
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1.
What is the main topic of John and Emily’s conversation?
How to build a decision tree model
The design of a new particle detector
A machine learning method for classifying particles
A comparison of different physics laboratories
Explanation:
John says he will explain their machine learning method for classifying particles from collision data.
2.
What machine learning model do they use?
A support vector machine
A logistic regression model
A deep neural network
A decision tree
Explanation:
John directly says, ‘We use a deep neural network.’
3.
Which features are most important for the model?
Color, mass, and distance
Energy, momentum, and particle type
Angle, time, and charge
Temperature, pressure, and speed
Explanation:
John lists the most important features as energy, momentum, and particle type.
4.
What can be inferred about the deep neural network in this conversation?
It is useful because it can handle complicated patterns
It does not require any data cleaning
It is less effective than decision trees for this task
It can only work with real experiment data
Explanation:
John explains that they chose a neural network because it handles complex patterns well.
5.
What will John and his team do next in their research?
Focus only on accuracy and ignore ROC curves
Stop using collision data and switch to interviews
Replace the neural network with a decision tree
Test the model on real experiment data
Explanation:
John says the next step is to test on real experiment data.
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