Worked on the oracle-samples/oci-data-science-ai-samples repository to deliver comprehensive developer documentation for the AI Quick Actions Time Series Forecasting feature. Focused on creating detailed guides that explain deployment workflows, request and response payload structures, and practical examples for both single and multi-time series forecasting scenarios. Utilized Markdown to structure the documentation and leveraged expertise in AI/ML and time series forecasting to clarify model context, data handling, and hardware requirements. The documentation aimed to streamline onboarding for developers and reduce support needs by providing clear, self-service resources, ultimately enhancing the usability and accessibility of the forecasting models.