Author: Namita Das

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 […]

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 […]

Amazon Forecast uses machine learning (ML) to generate more accurate demand forecasts, without requiring any prior ML experience. Forecast brings the same technology used at Amazon.com to developers as a fully managed service, removing the need to manage resources or rebuild your systems. To start generating forecasts through Forecast, you can follow three steps of […]

We’re excited to announce the Amazon Forecast Weather Index, which can increase your forecasting accuracy by automatically including local weather information in your demand forecasts with one click and at no extra cost. Weather conditions influence consumer demand patterns, product merchandizing decisions, staffing requirements, and energy consumption needs. However, acquiring, cleaning, and effectively using live […]

We’re excited to announce that you can now measure the accuracy of forecasts for individual items in Amazon Forecast, allowing you to better understand your forecasting model’s performance for the items that most impact your business. Improving forecast accuracy for specific items—such as those with higher prices or higher costs—is often more important than optimizing […]

September 2021: This blog has been updated to include three recently launched accuracy metrics in Amazon Forecast and the ability to select an accuracy metric to optimize AutoML. We’re excited to announce that you can now measure the accuracy of your forecasting model to optimize the trade-offs between under-forecasting and over-forecasting costs, giving you flexibility in […]

We’re excited to announce that Amazon Forecast can now use Convolutional Neural Networks (CNNs) to train forecasting models up to 2X faster with up to 30% higher accuracy. CNN algorithms are a class of neural network-based machine learning (ML) algorithms that play a vital role in Amazon.com’s demand forecasting system and enable Amazon.com to predict […]