AWS Machine Learning Blog
Category: Amazon Forecast
Choose specific timeseries to forecast with Amazon Forecast
Today, we’re excited to announce that Amazon Forecast offers the ability to generate forecasts on a selected subset of items. This helps you to leverage the full value of your data, and apply it selectively on your choice of items reducing the time and effort to get forecasted results. Generating a forecast on ‘all’ items of the […]
Read MoreWeekly forecasts can now start on Sunday with Amazon Forecast
We are excited to announce that in Amazon Forecast, you can now start your forecast horizon at custom starting points, including on Sundays for weekly forecasts. This allows you to more closely align demand planning forecasts to local business practices and operational requirements. Forecast is a fully managed service that uses statistical and machine learning […]
Read MoreContinuously monitor predictor accuracy with Amazon Forecast
We’re excited to announce that you can now automatically monitor the accuracy of your Amazon Forecast predictors over time. As new data is provided, Forecast automatically computes predictor accuracy metrics on the new dataset, providing you with more information to decide whether to keep using, retrain, or create new predictors. Monitoring predictor quality and identifying […]
Read MoreYour guide to AI and ML at AWS re:Invent 2021
It’s almost here! Only 9 days until AWS re:Invent 2021, and we’re very excited to share some highlights you might enjoy this year. The AI/ML team has been working hard to serve up some amazing content and this year, we have more session types for you to enjoy. Back in person, we now have chalk […]
Read MoreUnderstand drivers that influence your forecasts with explainability impact scores in Amazon Forecast
We’re excited to launch explainability impact scores in Amazon Forecast, which help you understand the factors that impact your forecasts for specific items and time durations of interest. Forecast is a managed service for developers that uses machine learning (ML) to generate more accurate demand forecasts, without requiring any ML experience. To increase forecast model […]
Read MoreNew Amazon Forecast API that creates up to 40% more accurate forecasts and provides explainability
We’re excited to announce a new forecasting API for Amazon Forecast that generates up to 40% more accurate forecasts and helps you understand which factors, such as price, holidays, weather, or item category, are most influencing your forecasts. Forecast uses machine learning (ML) to generate more accurate demand forecasts, without requiring any ML experience. Forecast […]
Read MoreCluster time series data for use with Amazon Forecast
In the era of Big Data, businesses are faced with a deluge of time series data. This data is not just available in high volumes, but is also highly nuanced. Amazon Forecast Deep Learning algorithms such as DeepAR+ and CNN-QR build representations that effectively capture common trends and patterns across these numerous time series. These […]
Read MoreAccurately predicting future sales at Clearly using Amazon Forecast
This post was cowritten by Ziv Pollak, Machine Learning Team Lead, and Alex Thoreux, Web Analyst at Clearly. A pioneer in online shopping, Clearly launched their first site in 2000. Since then, they’ve grown to become one of the biggest online eyewear retailers in the world, providing customers across Canada, the US, Australia and New […]
Read MorePrepare and clean your data for Amazon Forecast
You might use traditional methods to forecast future business outcomes, but these traditional methods are often not flexible enough to account for varying factors, such as weather or promotions, outside of the traditional time series data considered. With the advancement of machine learning (ML) and the elasticity that the AWS Cloud brings, you can now […]
Read MoreIntroducing hierarchical deletion to easily clean up unused resources in Amazon Forecast
Amazon Forecast just launched the ability to hierarchically delete resources at a parent level without having to locate the child resources. You can stay focused on building value-adding forecasting systems and not worry about trying to manage individual resources that are created in your workflow. Forecast uses machine learning (ML) to generate more accurate demand […]
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