.. _sphx_glr_auto_examples_applications:

.. _realworld_examples:

Examples based on real world datasets
-------------------------------------

Applications to real world problems with some medium sized datasets or
interactive user interface.



.. raw:: html

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


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example shows the reconstruction of an image from a set of parallel projections, acquired ...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_tomography_l1_reconstruction_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_tomography_l1_reconstruction.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Compressive sensing: tomography reconstruction with L1 prior (Lasso)</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="The dataset used in this example is a preprocessed excerpt of the &quot;Labeled Faces in the Wild&quot;, ...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_face_recognition_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_face_recognition.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Faces recognition example using eigenfaces and SVMs</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example shows how to use KernelPCA to denoise images. In short, we take advantage of the a...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_digits_denoising_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_digits_denoising.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Image denoising using kernel PCA</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example demonstrates how Polars-engineered lagged features can be used for time series for...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_time_series_lagged_features_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_time_series_lagged_features.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Lagged features for time series forecasting</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Demonstrate how model complexity influences both prediction accuracy and computational performa...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_model_complexity_influence_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_model_complexity_influence.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Model Complexity Influence</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This is an example showing how scikit-learn can be used for classification using an out-of-core...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_out_of_core_classification_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_out_of_core_classification.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Out-of-core classification of text documents</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example illustrates the need for robust covariance estimation on a real data set. It is us...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_outlier_detection_wine_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_outlier_detection_wine.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Outlier detection on a real data set</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This is an example showing the prediction latency of various scikit-learn estimators.">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_prediction_latency_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_prediction_latency.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Prediction Latency</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="Modeling species&#x27; geographic distributions is an important problem in conservation biology. In ...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_species_distribution_modeling_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_species_distribution_modeling.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Species distribution modeling</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This notebook introduces different strategies to leverage time-related features for a bike shar...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_cyclical_feature_engineering_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_cyclical_feature_engineering.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Time-related feature engineering</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This is an example of applying NMF and LatentDirichletAllocation on a corpus of documents and e...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_topics_extraction_with_nmf_lda_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_topics_extraction_with_nmf_lda.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Topic extraction with Non-negative Matrix Factorization and Latent Dirichlet Allocation</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="This example employs several unsupervised learning techniques to extract the stock market struc...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_plot_stock_market_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_plot_stock_market.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Visualizing the stock market structure</div>
    </div>


.. raw:: html

    <div class="sphx-glr-thumbcontainer" tooltip="A classical way to assert the relative importance of vertices in a graph is to compute the prin...">

.. only:: html

  .. image:: /auto_examples/applications/images/thumb/sphx_glr_wikipedia_principal_eigenvector_thumb.png
    :alt:

  :ref:`sphx_glr_auto_examples_applications_wikipedia_principal_eigenvector.py`

.. raw:: html

      <div class="sphx-glr-thumbnail-title">Wikipedia principal eigenvector</div>
    </div>


.. raw:: html

    </div>


.. toctree::
   :hidden:

   /auto_examples/applications/plot_tomography_l1_reconstruction
   /auto_examples/applications/plot_face_recognition
   /auto_examples/applications/plot_digits_denoising
   /auto_examples/applications/plot_time_series_lagged_features
   /auto_examples/applications/plot_model_complexity_influence
   /auto_examples/applications/plot_out_of_core_classification
   /auto_examples/applications/plot_outlier_detection_wine
   /auto_examples/applications/plot_prediction_latency
   /auto_examples/applications/plot_species_distribution_modeling
   /auto_examples/applications/plot_cyclical_feature_engineering
   /auto_examples/applications/plot_topics_extraction_with_nmf_lda
   /auto_examples/applications/plot_stock_market
   /auto_examples/applications/wikipedia_principal_eigenvector