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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_FeedForwardNetwork.ipynb
CNTK_103B_MNIST_FeedForwardNetwork.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_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_206_Basic_GAN.ipynb
CNTK_206_Basic_GAN.ipynb
 
 
CNTK_207_Training_with_Sampled_Softmax.ipynb
CNTK_207_Training_with_Sampled_Softmax.ipynb
 
 
README.md
README.md
 
 

README.md

Tutorials

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

Python

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

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 on the CNTK wiki.

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