This technical paper introduces forecasting, its terminology, challenges, and use cases. This document uses a case study to reinforce forecasting concepts, forecasting steps, and references how Amazon Forecast can help solve the many practical challenges in real-world forecasting problems.
Provides a conceptual overview of Amazon Forecast, includes detailed instructions for using the various features, and provides a complete API reference for developers.
You can find additional samples to get started with on GitHub.
Solution implementation example
The Improving Your Forecast with Machine Learning solution enables customers to bring models to production faster and with less overhead costs by generating, testing, comparing, and iterating on forecasts from Amazon Forecast. You can use this solution to accurately predict retail inventory demand, supply-chain planning, workforce status, web traffic forecasting, and more.