Amazon Forecast now supports what-if analyses

Amazon Forecast generates predictions for products with no historical data that is more accurate than before

Conduct what-if analyses with Amazon Forecast, up to 80% faster than before

Automate your time series forecasting in Snowflake using Amazon Forecast

Start your successful journey with time series forecasting with Amazon Forecast

Generate cold start forecasts for products with no historical data using Amazon Forecast, now up to 45% more accurate

Documentation

Technical Guide: 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.

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Developer Guide: Provides a conceptual overview of Amazon Forecast, includes detailed instructions for using the various features, and provides a complete API reference for developers.  

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You can find additional samples to get started with on GitHub.  

Solution Implementation: 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.

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Sample notebooks

You can find workshops, notebooks and MLOps samples to get started on Github.

Videos & tutorials

AWS re:Invent 2022 - How Taco Bell is improving digital availability with ML forecasting (AIM333)
Deploying No-Code Automated MLOps for Amazon Forecast - AWS Online Tech Talks

Blog posts & articles

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What's new

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Learn about Amazon Forecast pricing
Learn about Amazon Forecast pricing

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