Introducing Time-series Foundation Model

Forecasting is central to decisions in demand planning, energy, operations, and finance. Yet traditional forecasting workflows often require careful model selection, feature engineering, and dataset-specific training before they can be useful. Time-series foundation models offer a different starting point: a model pre-trained across a broad collection of time-series patterns that can produce forecasts for an unseen series with little or no task-specific training.

Join us for an technical session on AWS Chronos, a family of pretrained time-series forecasting models. We will unpack the core idea of zero-shot forecasting, walk through how historical signals become probabilistic forecasts, and discuss when these models are useful in a real forecasting workflow.

Slides for past meetups posted: Github
Recordings posted at: YanAITalk
Feel free to reach out if you want to present at upcoming meetups!

Note: You must have a Zoom account to login (free account is sufficient). Zoom Link will be posted to the event page one day before the meetup.