- Use cases
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1. Preprocessing
- SageMaker Object Detection preprocessing
- Rekognition Object Detection preprocessing
- SageMaker Kmeans preprocessing
- Autopilot preprocessing
- DeepAR preprocessing
- Personalize preprocessing
- Select, drop or extract Columns
- Split dataset to Train and Test
- Upload to s3
- Forecast preprocessing
- Rekognition Classification preprocessing
- SageMaker Image Classification preprocessing
- Xgboost preprocessing
- Blazingtext preprocessing
- Comprehend custom preprocessing
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2. Training
- SageMaker Object Detection training
- Rekognition Object Detection training
- Forecast training
- Personalize training
- BlazingText training
- DeepAR training
- SageMaker Kmeans training
- Comprehend custom training
- Autopilot Training
- Xgboost Training
- Autogluon training
- Rekognition Classification training
- SageMaker Image Classification training
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3. Inference
- SageMaker Object Detection inference
- Forecast inference
- Rekognition Object Detection inference
- Comprehend custom inference
- Personalize inference
- Autopilot Inference
- BlazingText Inference
- Custom SageMaker model Inference
- DeepAR Inference
- Rekognition Classification inference
- SageMaker Image Classification inference
- SageMaker Kmeans inference
- Xgboost Inference
- Contribute a use case or contact us for help.
- Frequently Asked Questions
Forecast inference
Make sure you saw this link for training first.
Once the training is complete or predictor is in “ACTIVE” state, and you are satisfied by its metrics, you can use it to create a forecast.
CLI
aws forecast create-forecast \
--forecast-name myforecast \
--predictor-arn arn:aws:forecast:<region>:<acct-id>:predictor/mypredictor
When the forecast is “ACTIVE”, you can query it to get predictions. You can export the whole forecast as a CSV file, or query for specific lookups.
CLI
aws forecastquery query-forecast \
--forecast-arn arn:aws:forecast:<region>:<acct-id>:forecast/myforecast \
--start-date <YYYY-MM-DDTHH:MM:SS> \
--end-date <YYYY-MM-DDTHH:MM:SS> \
--filters '{"item_id":"<value>"}'
To export the whole forecast as a CSV file to your S3 bucket:
CLI
aws forecast create-forecast-export-job \
--forecast-export-job-name myforecast_exportjob \
--forecast-arn arn:aws:forecast:<region>:<acct-id>:forecast/myforecast \
--destination S3Config="{Path='s3://<bucket>',RoleArn='arn:aws:iam::<acct-id>:role/<Role>'}"
Make sure sure the IAM role you provide has permission to write data to your S3 bucket