1.1Basic
Classify images and generate a new explanation.
Separate the model roles.
Choose two mappings.
× Incorrect
A discriminative model predicts classes or scores, while a generative model creates new content from a learned distribution.
Detailed explanation
CorrectUse a discriminative model for a class or probability decision
It learns a decision boundary or score.
It learns a decision boundary or score.
CorrectUse a generative model to create new text or images
It generates content from a learned distribution.
It generates content from a learned distribution.
IncorrectA discriminative model always writes new text
It predicts or scores.
It predicts or scores.
IncorrectGenerated content is always a copy of training data
New combinations can be produced.
New combinations can be produced.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 1.1の判別モデル、生成モデル、AIタスクを確認する。Expected result
判定と生成の目的に応じてモデルの種類を選べる。Key points
- Discriminative
- Generative
- Output
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Command output formatting can vary slightly by distribution or tool version.
- Run the example in a temporary directory or process when possible.
Foundation review
Read the scope first
Check whether the command acts on the current shell, a new process, an existing process, or a file.
Verify the observable result
Use the supplied command and compare the output with the expected result.
Question IDAWS-AIF-392
EnvironmentAWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
Last technical review2026-08-20
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