Add probabilistic ML dashboard (React + FastAPI)

[Shristimishra980]

Reference Issues/PRs

What does this implement/fix? Explain your changes.

This PR introduces a brand new full-stack dashboard for the skpro library. This dashboard allows users to interactively explore, visualize, and compare the uncertainty estimates of different probabilistic models. The dashboard includes:
Backend (skpro/dashboard/backend/): A FastAPI application that serves the available models (
main.py, models.py) and handles model fitting and prediction with uncertainty intervals via API endpoints (/upload, /predict, /compare).
Frontend (skpro/dashboard/frontend/): A React application utilizing recharts to render confidence bands, prediction charts, and side-by-side model metric comparisons.
Sample Datasets: A set of sample CSV files to easily test the application functionality.

Does your contribution introduce a new dependency? If yes, which one?

Yes, but they are isolated. The dashboard relies on fastapi, uvicorn, pandas, and react/npm for the frontend. These dependencies are strictly isolated inside the skpro/dashboard folder and do not add to the external dependencies of the core skpro package.

What should a reviewer concentrate their feedback on?

Reviewing the structural placement of the dashboard/ folder. If the core team prefers this to be a standalone repository (e.g. sktime/skpro-dashboard), let me know!
The implementations and API wrappers around BayesianRidge, GaussianProcessRegressor, QuantileRegressor, and GradientBoostingRegressor in models.py Feedback on visual layout for the React frontend.

Did you add any tests for the change?

There are no automated unit tests included in this PR due to its nature as a standalone dashboard. Verified locally through end-to-end manual testing of:
Starting up backend and frontend simultaneously.
Uploading sample datasets and evaluating predictions.

Any other comments?

N/A

PR checklist

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For new estimators

• I've added the estimator to the API reference - in docs/source/api_reference/taskname.rst, follow the pattern.
• I've added one or more illustrative usage examples to the docstring, in a pydocstyle compliant Examples section.
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  dependency isolation, see the estimator dependencies guide.