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.. * Copyright 2021 Intel Corporation
.. *
.. * Licensed under the Apache License, Version 2.0 (the "License");
.. * you may not use this file except in compliance with the License.
.. * You may obtain a copy of the License at
.. *
.. *     http://www.apache.org/licenses/LICENSE-2.0
.. *
.. * Unless required by applicable law or agreed to in writing, software
.. * distributed under the License is distributed on an "AS IS" BASIS,
.. * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
.. * See the License for the specific language governing permissions and
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.. |automl_with_intelex_jun| replace:: AutoML MultiClass Classification (Gradient Boosting, Random Forest, kNN) using AutoGluon with |intelex| 
.. _automl_with_intelex_jun: https://www.kaggle.com/alex97andreev/tps-jun-autogluon-with-sklearnex

.. |automl_with_intelex_tps_oct| replace:: AutoML Binary Classification (Gradient Boosting, Random Forest) using AutoGluon with |intelex|
.. _automl_with_intelex_tps_oct: https://www.kaggle.com/lordozvlad/fast-automl-with-intel-extension-for-scikit-learn/notebook

.. |automl_with_intelex_tps_nov| replace:: AutoML Binary Classification (Gradient Boosting, Random Forest, kNN) using EvalML and AutoGluon with |intelex|
.. _automl_with_intelex_tps_nov: https://www.kaggle.com/lordozvlad/tps-nov-automl-with-intel-extension

.. |automl_with_intelex_titanic| replace:: AutoML Binary Classification (Gradient Boosting, Random Forest, kNN) using AutoGluon with |intelex|
.. _automl_with_intelex_titanic: https://www.kaggle.com/lordozvlad/titanic-automl-with-intel-extension-for-sklearn/notebook

.. |automl_with_intelex_tps_jan| replace:: AutoML Binary Classification (Random Forest, SVR, Blending) using PyCaret with |intelex|
.. _automl_with_intelex_tps_jan: https://www.kaggle.com/code/lordozvlad/tps-jan-fast-pycaret-with-scikit-learn-intelex/notebook


Kaggle Kernels that use AutoML and |intelex|
--------------------------------------------

The following Kaggle kernels show how to patch autoML framewokrs with |intelex|.

.. include:: /kaggle/note-about-tps.rst

.. list-table::
   :header-rows: 1
   :align: left
   :widths: 40 20

   * - Kernel
     - Goal
   * - |automl_with_intelex_jun|_

       **Data:** [TPS Jun 2021] Synthetic eCommerce data
     - Predict the category of an eCommerce product
   * - |automl_with_intelex_titanic|_

       **Data:** Titanic datset
     - Predict whether a passenger survivies
   * - |automl_with_intelex_tps_oct|_

       **Data:** [TPS Oct 2021] Synthetic molecular response data
     - Predict the biological response of molecules given various chemical properties
   * - |automl_with_intelex_tps_nov|_

       **Data:** [TPS Nov 2021] Synthetic spam emails data
     - Identify spam emails via features extraced from the email
   * - |automl_with_intelex_tps_jan|_

       **Data:** [TPS Jan 2022] Fictional Sales data
     - Predict the corresponding item sales for each date-country-store-item combination