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Notebooks and examples on how to onboard and use various features of Amazon Forecast

This is a place where you will find various examples covering Amazon Forecast best practices

Open the notebooks folder to find a CloudFormation template that will deploy all the resources you need to build your first campaign with Amazon Personalize. The notebooks provided can also serve as a template to building your own models with your own data.

In the notebooks folder you will learn to:

1. Prepare a dataset for use with Amazon Forecast.
2. Build models based on that dataset.
3. Evaluate a model's performance based on real observations.
4. How to evaluate the value of a Forecast compared to another.

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:

1. 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.