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[DOC] Finished first two Bayesian notebooks and their artefacts #520

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Reference Issues/PRs

Provides example for Bayesian Conjugate Linear Regressor #500

What does this implement/fix? Explain your changes.

This contribution includes the first two notebooks in a planned series of four. These two notebooks cover:

  1. The general theory behind Bayesian Linear Regression.
  2. The conjugate prior method for solving Bayesian Linear Regression and implementation of this approach using the BayesianConjugateLinearRegressor estimator.
    In addition, lightweight utils.py and small synthetic dataset are included.

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

None

What should a reviewer concentrate their feedback on?

Correctness of exposition

Did you add any tests for the change?

No

Any other comments?

No

PR checklist

No

For all contributions
  • I've added myself to the list of contributors with any new badges I've earned :-)
    How to: add yourself to the all-contributors file in the skpro root directory (not the CONTRIBUTORS.md). Common badges: code - fixing a bug, or adding code logic. doc - writing or improving documentation or docstrings. bug - reporting or diagnosing a bug (get this plus code if you also fixed the bug in the PR).maintenance - CI, test framework, release.
    See here for full badge reference
  • The PR title starts with either [ENH], [MNT], [DOC], or [BUG]. [BUG] - bugfix, [MNT] - CI, test framework, [ENH] - adding or improving code, [DOC] - writing or improving documentation or docstrings.
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.
  • If the estimator relies on a soft dependency, I've set the python_dependencies tag and ensured
    dependency isolation, see the estimator dependencies guide.

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@meraldoantonio
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Hi @fkiraly,

This PR includes the first two example notebooks for the Bayesian estimators. I suggest we merge these first, and I can submit the remaining notebooks, which are still in progress, in a separate PR.

I haven’t made any major changes to these notebooks since your review in the old PR (#500).

Let me know your thoughts or if I need to make any change to this PR, thanks!

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