Notebooks and examples on how to onboard and use various features of Amazon Forecast.
Notebooks provide an interactive environment combining code and documentation, which can be a useful way to first get familiar with Amazon Forecast - as well as when exploring more advanced topics.
Open the notebooks/ folder to find:
- A CloudFormation template that will deploy all the resources you need to start exploring Amazon Forecast via notebooks with Amazon SageMaker
- Worked examples for getting started with Amazon Forecast: Preparing your data, and building and evaluating predictors.
- More advanced examples covering a range of topics like what-if analysis.
This is a place where you will find various examples covering Machine Learning Operations best practices.
To get started navigate to the ml_ops/ folder and follow the README instructions.
In the ml_ops folder you will learn how to:
- Deploy an automated end to end pipeline from training to visualization of your Amazon Forecasts in Amazon QuickSight
This sample code is made available under a modified MIT license. See the LICENSE file.