A retailer has historical sales and seasonality by store, product, and date.
It wants to estimate next week's quantity for purchasing.
Which AI use case best fits this requirement?
Estimating a future quantity from observations ordered by time is time-series forecasting.
Detailed explanation
Historical time-ordered sales can be used to estimate future quantities.
Historical time-ordered sales can be used to estimate future quantities.
Summarization generates shorter text, not future sales quantities.
Summarization generates shorter text, not future sales quantities.
Authentication verifies identity and does not forecast demand.
Authentication verifies identity and does not forecast demand.
Compression reduces storage size and does not estimate future demand.
Compression reduces storage size and does not estimate future demand.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01ガイドのDomain 1.2で予測タスクと生成タスクの違いを確認する。Expected result
将来の数値を推定する予測と、文章生成・認証・圧縮を区別できる。Key points
- Time series
- Future values
- Continuous prediction
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.