Examples
========

CNTK also offers several examples that are not in Tutorial style. 
Many of these are recipes involve more advanced networks and are located under :cntk:`Examples directory <Examples/>`.

-  :cntk:`MNIST <Examples/Image/Classification/MLP/Python/SimpleMNIST.py>`:
   A fully connected feed-forward model for classification of MNIST
   images. (Follow the instructions in
   :cntk:`Examples/Image/DataSets/MNIST/README.md` to get the MNIST data set)

-  :cntk:`TrainResNet_CIFAR10 <Examples/Image/Classification/ResNet/Python/TrainResNet_CIFAR10.py>`:
   An image classification ResNet model for training on the CIFAR image
   dataset. (Follow the instructions in
   :cntk:`Examples/Image/DataSets/CIFAR-10/README.md` to get the CIFAR dataset
   and convert it to the CNTK supported format)

-  :cntk:`SequenceClassification <Examples/SequenceClassification/SimpleExample/Python/SequenceClassification.py>`:
   An LSTM sequence classification model for text data.

-  :cntk:`Sequence2Sequence <Examples/SequenceToSequence/CMUDict/Python/Sequence2Sequence.py>`:
   A sequence to sequence grapheme to phoneme translation model that
   trains on the CMUDict corpus.

-  :cntk:`NumpyInterop <Examples/LanguageUnderstanding/ATIS/Python/LanguageUnderstanding.py>`
   - Language Understanding.

-  :cntk:`Video <Examples/Video/GettingStarted/Python/Conv3D_UCF11.py>`
   - Basic 3D convolution networks for deep learning on video tasks.