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Fix typo and link formatting in FAQ #1195

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Jul 30, 2021
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Fix typo and link formatting in FAQ #1195

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6 changes: 3 additions & 3 deletions doc/faq.rst
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Expand Up @@ -213,7 +213,7 @@ Auto-sklearn wraps scikit-learn and therefore inherits its parallelism implement
scikit-learn uses two modes of parallelizing computations:

1. By using joblib to distribute independent function calls on multiple cores.
2. By using lower level libraries such as OpenML and numpy to distribute more fine-grained
2. By using lower level libraries such as OpenMP and numpy to distribute more fine-grained
computation.

This means that Auto-sklearn can use more resources than expected by the user. For technical
Expand All @@ -225,7 +225,7 @@ with the number of requested CPUs). This can be done by setting the following en
variables: ``MKL_NUM_THREADS``, ``OPENBLAS_NUM_THREADS``, ``BLIS_NUM_THREADS`` and
``OMP_NUM_THREADS``.

More details can be found in the `scikit-learn docs <https://scikit-learn.org/stable/computing/parallelism.html?highlight=joblib#parallelism>`
More details can be found in the `scikit-learn docs <https://scikit-learn.org/stable/computing/parallelism.html?highlight=joblib#parallelism>`_.

Meta-Learning
=============
Expand All @@ -236,7 +236,7 @@ Which datasets are used for meta-learning?
We updated the list of datasets used for meta-learning several times and this list now differs
significantly from the original 140 datasets we used in 2015 when the paper and the package were
released. An up-to-date list of `OpenML task IDs <https://docs.openml.org/#tasks>`_ can be found
on `github <https://github.com/automl/auto-sklearn/blob/master/scripts/update_metadata_util.py>`_
on `github <https://github.com/automl/auto-sklearn/blob/master/scripts/update_metadata_util.py>`_.

How can datasets from the meta-data be excluded?
------------------------------------------------
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