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 Getting Started Tutorial. The tutorial guides you through the core steps of Forecast from start to finish.

For basic tutorials for specific processes, refer to the following Python notebooks:

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

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

  3. Retraining predictors - Retrain an existing predictor with updated data.

  4. Upgrade to AutoPredictor - Upgrade legacy predictors to AutoPredictor.

  5. Clean Up - Delete the dataset groups, predictors, forecasts created during the tutorials.

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

Advanced Tutorials

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