# Flight delay prediction

> Flight delay prediction - Designed for DataRobot trial users, experience an end-to-end DataRobot
> workflow using a use case that predicts flight delays.

This Markdown file sits beside the HTML page at the same path (with a `.md` suffix). It summarizes the topic and lists links for tools and LLM context.

Companion generated at `2026-05-06T18:17:09.585012+00:00` (UTC).

## Primary page

- [Flight delay prediction](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/time-series/flight-delays.html): Full documentation for this topic (HTML).

## Related documentation

- [Developer documentation](https://docs.datarobot.com/en/docs/api/index.html): Linked from this page.
- [Developer learning](https://docs.datarobot.com/en/docs/api/dev-learning/index.html): Linked from this page.
- [AI accelerators](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/index.html): Linked from this page.
- [Time series and specific use cases](https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/time-series/index.html): Linked from this page.

## Documentation content

[Access this AI accelerator on GitHub](https://github.com/datarobot-community/ai-accelerators/blob/main/advanced_ml_and_api_approaches/Flight%20Delays%20-%20Starter%20Use%20Case%20for%20New%20DataRobot%20Users/Flight%20Delays%20-%20Starter%20Use%20Case%20for%20New%20DataRobot%20Users.ipynb)

This accelerator aims to assist DataRobot trial users by providing a guided walkthough of the trial experience. DataRobot suggests that you complete the Flight Delays sample use case in the graphical user interface first, and then return to this accelerator.

In this notebook, you will:

- Create a Use Case.
- Import data from an S3 bucket (this differs from the UI walkthrough).
- Perform a data wrangling operation to create the target feature with code (this also differs from the UI walkthrough).
- Register the wrangled data set.
- Explore the new data set.
- Create an experiment and allow DataRobot automation to populate it with many modeling pipelines.
- Explore model insights for the best performing model.
- View the modeling pipeline for the best performing model.
- Register a model in Registry.
- Configure a deployment.
- Create a deployment.
- Make predictions using the deployment.
- Review deployment metrics.