Getting Started (Python Notebooks) - Amazon Forecast

Getting Started (Python Notebooks)

Note

For a complete list of tutorials using Python notebooks, see the Amazon Forecast Github Samples page.

To get started using Amazon Forecast APIs with Python notebooks, see the Basic Tutorial. The tutorial guides you through the core steps of Forecast from start to finish:

  1. Preparing data - Prepare a dataset, create a dataset group, define the schema, and import the dataset group.

  2. Training predictors - Create a predictor, evaluate error metrics, and generate forecasts.

  3. Evaluating predictors - Obtain predictions, visualize predictions, and compare results.

After completing the tutorial, you can use the Clean Up tutorial to delete the dataset groups, predictors, forecasts created during the tutorial.

To repeat this tutorial with AutoML, see Getting Started with AutoML.

Advanced Tutorials

For more advanced tutorials, refer to the following Python notebooks: