.. _sphx_glr_auto_examples_expressions:

.. _expressions_examples_ref:

Skrub expressions
=================



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    <div class="sphx-glr-thumbnails">

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    <div class="sphx-glr-thumbcontainer" tooltip="In this example, we show a simple pipeline handling a dataset with 2 tables, which would be difficult to implement, validate, and deploy correctly without skrub.">

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  .. image:: /auto_examples/expressions/images/thumb/sphx_glr_10_expressions_intro_thumb.svg
    :alt:

  :ref:`sphx_glr_auto_examples_expressions_10_expressions_intro.py`

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      <div class="sphx-glr-thumbnail-title">Building complex tabular pipelines</div>
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    <div class="sphx-glr-thumbcontainer" tooltip="Our machine-learning pipeline typically contains some values or choices which may influence its prediction performance, such as hyperparameters (e.g. the regularization parameter alpha of a RidgeClassifier, the learning_rate of a HistGradientBoostingClassifier), which estimator to use (e.g. RidgeClassifier or HistGradientBoostingClassifier), or which steps to include (e.g. should we join a table to bring additional information or not).">

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  .. image:: /auto_examples/expressions/images/thumb/sphx_glr_11_choices_thumb.svg
    :alt:

  :ref:`sphx_glr_auto_examples_expressions_11_choices.py`

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      <div class="sphx-glr-thumbnail-title">Tuning pipelines</div>
    </div>


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    </div>


.. toctree::
   :hidden:

   /auto_examples/expressions/10_expressions_intro
   /auto_examples/expressions/11_choices