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DOC [PST] tune FAQ page styling #28448

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46 changes: 39 additions & 7 deletions doc/faq.rst
Original file line number Diff line number Diff line change
@@ -1,3 +1,32 @@
.. raw:: html

<style>
/* h3 headings on this page are the questions; make them rubric-like */
h3 {
font-size: 1rem;
font-weight: bold;
padding-bottom: 0.2rem;
margin: 2rem 0 1.15rem 0;
border-bottom: 1px solid var(--pst-color-border);
}

/* Increase top margin for first question in each section */
h2 + section > h3 {
margin-top: 2.5rem;
}

/* Make the headerlinks a bit more visible */
h3 > a.headerlink {
font-size: 0.9rem;
}

/* Remove the backlink decoration on the titles */
h2 > a.toc-backref,
h3 > a.toc-backref {
text-decoration: none;
}
</style>

.. _faq:

==========================
Expand All @@ -9,8 +38,9 @@ Frequently Asked Questions
Here we try to give some answers to questions that regularly pop up on the mailing list.

.. contents:: Table of Contents
:local:
:depth: 2
:local:
:depth: 2


About the project
-----------------
Expand Down Expand Up @@ -313,12 +343,14 @@ Using scikit-learn

What's the best way to get help on scikit-learn usage?
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
**For general machine learning questions**, please use
`Cross Validated <https://stats.stackexchange.com/>`_ with the ``[machine-learning]`` tag.

**For scikit-learn usage questions**, please use `Stack Overflow <https://stackoverflow.com/questions/tagged/scikit-learn>`_
with the ``[scikit-learn]`` and ``[python]`` tags. You can alternatively use the `mailing list
<https://mail.python.org/mailman/listinfo/scikit-learn>`_.
* General machine learning questions: use `Cross Validated
<https://stats.stackexchange.com/>`_ with the ``[machine-learning]`` tag.

* scikit-learn usage questions: use `Stack Overflow
<https://stackoverflow.com/questions/tagged/scikit-learn>`_ with the
``[scikit-learn]`` and ``[python]`` tags. You can alternatively use the `mailing list
<https://mail.python.org/mailman/listinfo/scikit-learn>`_.

Please make sure to include a minimal reproduction code snippet (ideally shorter
than 10 lines) that highlights your problem on a toy dataset (for instance from
Expand Down