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:
- Prepare a dataset for use with Amazon Forecast.
- Build models based on that dataset.
- Evaluate a model's performance based on real observations.
- 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:
- 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.