AI Associate AI Fundamentals Practice Question
Which statement best describes 'inference' in the context of machine learning?
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
The process of using a trained model to make predictions on new data
Inference is the process of using a trained model to make predictions on new data. Training is the learning phase, and evaluation is assessing performance. Data collection is separate.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The process of training a model on labeled data
Why it's wrong here
That is training, not inference.
- ✗
The process of collecting and preparing data
Why it's wrong here
Data preparation precedes training and inference.
- ✓
The process of using a trained model to make predictions on new data
Why this is correct
Inference is applying the model to new, unseen data.
- ✗
The process of evaluating a model's accuracy
Why it's wrong here
Evaluation is a separate step after inference on a test set.
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