Amazon Forecast Documentation

Amazon Forecast includes AutoML capabilities that help to take care of the machine learning for you. Once you provide your data into Amazon S3, you can use Amazon Forecast to load and inspect the data, select the right algorithms, train a model, provide accuracy metrics, and generate forecasts. 

Amazon Forecast tracks the accuracy of your model over time as new data is imported. You can quantify your model’s deviation from initial quality metrics and make more informed decisions about keeping, retraining, or rebuilding the model as new data comes in.  

Explore what factors, such as price, holidays or weather, are driving your forecasts with Amazon Forecast, which provides forecast Explainability report in the form of impact scores for your forecasts, specific time series of interest or specific time durations. Explainability provides you more insight into better managing your business operations. 

With Weather Index, Amazon Forecast can increase your forecasting accuracy by ingesting local weather information in your demand forecasts. Weather conditions influence consumer demand patterns, product merchandizing decisions, staffing requirements, and energy consumption needs. When you use the Weather Index, Forecast trains a model with historical weather information for the locations of your operations and uses the latest weather forecasts on items that are influenced by day-to-day variations to create demand forecasts.

Amazon Forecast generates probabilistic forecasts at varying quantities. In addition, you can choose quantiles, including the 'mean' forecast.  

Amazon Forecast can use historical time series data (e.g., price, promotions, economic performance metrics) to help create accurate forecasts for your business. 

With the ability to focus your forecasts on only a subset of items in your dataset, you can train your model with all of your data, then apply it selectively to the subset of items most important to your business objectives.

Amazon Forecast provides accuracy metrics to help you understand the performance of your forecasting model and compare it to previous forecasting models you’ve created that may have looked at a different set of variables or used a different period of time for the historical data. Amazon Forecast allows you to create multiple backtest windows and visualize the metrics, helping you evaluate model accuracy over different start dates.

Amazon Forecast can be imported into common business and supply chain applications, allowing you to integrate forecasting into your existing business processes.

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