HAQM Forecast now supports what-if analyses

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

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

Automate your time series forecasting in Snowflake using HAQM Forecast

Start your successful journey with time series forecasting with HAQM Forecast

Generate cold start forecasts for products with no historical data using HAQM 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 HAQM Forecast can help solve the many practical challenges in real-world forecasting problems.

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Developer Guide: Provides a conceptual overview of HAQM 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 HAQM 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 HAQM Forecast - AWS Online Tech Talks

Blog posts & articles

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What's new

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Learn about HAQM Forecast pricing
Learn about HAQM Forecast pricing

Pay only for what you use, and there are no minimum fees and no upfront commitments.

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