Deep Papers
Demystifying Chronos: Learning the Language of Time Series
This week, we’ve covering Amazon’s time series model: Chronos. Developing accurate machine-learning-based forecasting models has traditionally required substantial dataset-specific tuning and model customization. Chronos however, is built on a language model architecture and trained with billions of tokenized time series observations, enabling it to provide accurate zero-shot forecasts matching or exceeding purpose-built models.
We dive into time series forecasting, some recent research our team has done, and take a community pulse on what people think of Chronos.
To learn more about ML observability, join the Arize AI Slack community or get the latest on our LinkedIn and Twitter.
This week, we’ve covering Amazon’s time series model: Chronos. Developing accurate machine-learning-based forecasting models has traditionally required substantial dataset-specific tuning and model customization. Chronos however, is built on a language model architecture and trained with billions of tokenized time series observations, enabling it to provide accurate zero-shot forecasts matching or exceeding purpose-built models.
We dive into time series forecasting, some recent research our team has done, and take a community pulse on what people think of Chronos.
To learn more about ML observability, join the Arize AI Slack community or get the latest on our LinkedIn and Twitter.