:orphan:



.. _sphx_glr_build_examples_classification:

Image Classification
====================



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    <div class="sphx-glr-thumbcontainer" tooltip="`CIFAR10 &lt;https://www.cs.toronto.edu/~kriz/cifar.html&gt;`__ is a dataset of tiny (32x32) images w...">

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 .. figure:: /build/examples_classification/images/thumb/sphx_glr_demo_cifar10_thumb.png
     :alt: 1. Getting Started with Pre-trained Model on CIFAR10

     :ref:`sphx_glr_build_examples_classification_demo_cifar10.py`

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    </div>


.. toctree::
   :hidden:

   /build/examples_classification/demo_cifar10

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    <div class="sphx-glr-thumbcontainer" tooltip="Hope you enjoyed playing with our demo script. Now, you may be wandering: how exactly was the m...">

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 .. figure:: /build/examples_classification/images/thumb/sphx_glr_dive_deep_cifar10_thumb.png
     :alt: 2. Dive Deep into Training with CIFAR10

     :ref:`sphx_glr_build_examples_classification_dive_deep_cifar10.py`

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    </div>


.. toctree::
   :hidden:

   /build/examples_classification/dive_deep_cifar10

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    <div class="sphx-glr-thumbcontainer" tooltip="`ImageNet &lt;http://www.image-net.org/&gt;`__ is a large labeled dataset of real-world images. It is...">

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 .. figure:: /build/examples_classification/images/thumb/sphx_glr_demo_imagenet_thumb.png
     :alt: 3. Getting Started with Pre-trained Models on ImageNet

     :ref:`sphx_glr_build_examples_classification_demo_imagenet.py`

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    </div>


.. toctree::
   :hidden:

   /build/examples_classification/demo_imagenet

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    <div class="sphx-glr-thumbcontainer" tooltip="Dataset size is a big factor in the performance of deep learning models. ImageNet has over one ...">

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 .. figure:: /build/examples_classification/images/thumb/sphx_glr_transfer_learning_minc_thumb.png
     :alt: 4. Transfer Learning with Your Own Image Dataset

     :ref:`sphx_glr_build_examples_classification_transfer_learning_minc.py`

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    </div>


.. toctree::
   :hidden:

   /build/examples_classification/transfer_learning_minc

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    <div class="sphx-glr-thumbcontainer" tooltip="ImageNet is the most well-known dataset for image classification. Since it was published, most ...">

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 .. figure:: /build/examples_classification/images/thumb/sphx_glr_dive_deep_imagenet_thumb.png
     :alt: 5. Train Your Own Model on ImageNet

     :ref:`sphx_glr_build_examples_classification_dive_deep_imagenet.py`

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    </div>


.. toctree::
   :hidden:

   /build/examples_classification/dive_deep_imagenet
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    <div class="sphx-glr-clear"></div>



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 .. container:: sphx-glr-footer
    :class: sphx-glr-footer-gallery


  .. container:: sphx-glr-download sphx-glr-download-python

    :download:`Download all examples in Python source code: examples_classification_python.zip </build/examples_classification/examples_classification_python.zip>`



  .. container:: sphx-glr-download sphx-glr-download-jupyter

    :download:`Download all examples in Jupyter notebooks: examples_classification_jupyter.zip </build/examples_classification/examples_classification_jupyter.zip>`


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 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_