Amazon Forecast uses machine learning (ML) to generate more accurate demand forecasts, without requiring any prior ML experience. Forecast brings the same technology used at to developers as a fully managed service, removing the need to manage resources or rebuild your systems.
To start generating forecasts through Forecast, you can follow three steps of importing your data, training and evaluating a predictor, and then generating forecasts. Starting today, you can now stop an in-progress Forecast resource workflow if you have mistakenly started a job or misconfigured a workflow before starting, giving you more flexibility to manage your Forecast workflows and to experiment.
Previously, because you couldn’t stop APIs in progress, you had to wait for the job to complete and would incur charges for the job. You can now easily stop the following Forecast resource workflows:

Dataset group import (CreateDatasetImportJob)
Predictor training (CreatePredictor)
Predictor backtest

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