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FunctionalAPI
FunctionalAPI
 
 
HelloWorld-LogisticRegression
HelloWorld-LogisticRegression
 
 
ImageHandsOn
ImageHandsOn
 
 
NumpyInterop
NumpyInterop
 
 
SLUHandsOn
SLUHandsOn
 
 
CNTK_101_LogisticRegression.ipynb
CNTK_101_LogisticRegression.ipynb
 
 
CNTK_102_FeedForward.ipynb
CNTK_102_FeedForward.ipynb
 
 
CNTK_103A_MNIST_DataLoader.ipynb
CNTK_103A_MNIST_DataLoader.ipynb
 
 
CNTK_103B_MNIST_LogisticRegression.ipynb
CNTK_103B_MNIST_LogisticRegression.ipynb
 
 
CNTK_103C_MNIST_MultiLayerPerceptron.ipynb
CNTK_103C_MNIST_MultiLayerPerceptron.ipynb
 
 
CNTK_103D_MNIST_ConvolutionalNeuralNetwork.ipynb
CNTK_103D_MNIST_ConvolutionalNeuralNetwork.ipynb
 
 
CNTK_104_Finance_Timeseries_Basic_with_Pandas_Numpy.ipynb
CNTK_104_Finance_Timeseries_Basic_with_Pandas_Numpy.ipynb
 
 
CNTK_105_Basic_Autoencoder_for_Dimensionality_Reduction.ipynb
CNTK_105_Basic_Autoencoder_for_Dimensionality_Reduction.ipynb
 
 
CNTK_106A_LSTM_Timeseries_with_Simulated_Data.ipynb
CNTK_106A_LSTM_Timeseries_with_Simulated_Data.ipynb
 
 
CNTK_106B_LSTM_Timeseries_with_IOT_Data.ipynb
CNTK_106B_LSTM_Timeseries_with_IOT_Data.ipynb
 
 
CNTK_200_GuidedTour.ipynb
CNTK_200_GuidedTour.ipynb
 
 
CNTK_201A_CIFAR-10_DataLoader.ipynb
CNTK_201A_CIFAR-10_DataLoader.ipynb
 
 
CNTK_201B_CIFAR-10_ImageHandsOn.ipynb
CNTK_201B_CIFAR-10_ImageHandsOn.ipynb
 
 
CNTK_202_Language_Understanding.ipynb
CNTK_202_Language_Understanding.ipynb
 
 
CNTK_203_Reinforcement_Learning_Basics.ipynb
CNTK_203_Reinforcement_Learning_Basics.ipynb
 
 
CNTK_204_Sequence_To_Sequence.ipynb
CNTK_204_Sequence_To_Sequence.ipynb
 
 
CNTK_205_Artistic_Style_Transfer.ipynb
CNTK_205_Artistic_Style_Transfer.ipynb
 
 
CNTK_206A_Basic_GAN.ipynb
CNTK_206A_Basic_GAN.ipynb
 
 
CNTK_206B_DCGAN.ipynb
CNTK_206B_DCGAN.ipynb
 
 
CNTK_206C_WGAN_LSGAN.ipynb
CNTK_206C_WGAN_LSGAN.ipynb
 
 
CNTK_207_Training_with_Sampled_Softmax.ipynb
CNTK_207_Training_with_Sampled_Softmax.ipynb
 
 
CNTK_208_Speech_Connectionist_Temporal_Classification.ipynb
CNTK_208_Speech_Connectionist_Temporal_Classification.ipynb
 
 
CNTK_301_Image_Recognition_with_Deep_Transfer_Learning.ipynb
CNTK_301_Image_Recognition_with_Deep_Transfer_Learning.ipynb
 
 
CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.ipynb
CNTK_302A_Evaluation_of_Pretrained_Super-resolution_Models.ipynb
 
 
CNTK_302B_Image_Super-resolution_Using_CNNs_and_GANs.ipynb
CNTK_302B_Image_Super-resolution_Using_CNNs_and_GANs.ipynb
 
 
CNTK_303_Deep_Structured_Semantic_Modeling_with_LSTM_Networks.ipynb
CNTK_303_Deep_Structured_Semantic_Modeling_with_LSTM_Networks.ipynb
 
 
CNTK_599A_Sequence_To_Sequence.ipynb
CNTK_599A_Sequence_To_Sequence.ipynb
 
 
README.md
README.md
 
 

README.md

Tutorials

In this folder you will find several tutorials both for the CNTK Python API, the Python Functional API, and for BrainScript.

Python

The Python Jupyter notebooks in this folder cover a range of different applications including image classification, language understanding, reinforcement learning and others. Additionally, the folder NumpyInterop contains a simple example on how to use numpy arrays as input for CNTK training and evaluation.

Functional API (still Python)

The FunctionalAPI folder is the staging area for Tutorials written using the Python Functional API. The plan is to have each Tutorial in this folder translated to a more succinct style in the FunctionalAPI folder. All FunctionalAPI Tutorials are fully tested, same as the Tutorials here.

BrainScript

There are four detailed tutorials on how to use CNTK with BrainScript. A step-by-step walk through for each of these is provided in the documentation.

  • Hello World - Logistic Regression (Details)
  • Image Hands On (Details)
  • SLU (Language Understanding) Hands On (Details)
  • Object detection using Fast R-CNN (Code, Details)