История

Project Philly 3ac55535fc Integrate alrezni/v2_default_unit_gain into master		2017-01-20 02:48:55 -08:00
..
HelloWorld-LogisticRegression	Update README.md	2016-11-14 21:19:20 +01:00
ImageHandsOn	Revision based on CR.	2017-01-13 08:52:37 -08:00
NumpyInterop	Integrate alrezni/v2_scratch into master	2016-11-14 10:59:42 -08:00
SLUHandsOn	…
CNTK_101_LogisticRegression.ipynb	Bump version	2017-01-16 20:15:06 +01:00
CNTK_102_FeedForward.ipynb	Updates to CNTK 102 and 103B with CR feedback	2017-01-18 13:58:58 -08:00
CNTK_103A_MNIST_DataLoader.ipynb	Bump version	2017-01-16 20:15:06 +01:00
CNTK_103B_MNIST_FeedForwardNetwork.ipynb	Updates to CNTK 102 and 103B with CR feedback	2017-01-18 13:58:58 -08:00
CNTK_104_Finance_Timeseries_Basic_with_Pandas_Numpy.ipynb	Make Jupyter Notebook tests device-aware	2017-01-12 13:59:56 +01:00
CNTK_105_Basic_Autoencoder_for_Dimensionality_Reduction.ipynb	Add a default (true) for the unit-gain flag value	2017-01-20 09:27:36 +01:00
CNTK_106A_LSTM_Timeseries_with_Simulated_Data.ipynb	Updated tutorial with CR feedback	2017-01-19 13:05:33 -08:00
CNTK_201A_CIFAR-10_DataLoader.ipynb	Tutorials: more fixes	2016-11-18 19:15:15 +01:00
CNTK_201B_CIFAR-10_ImageHandsOn.ipynb	Add a default (true) for the unit-gain flag value	2017-01-20 09:27:36 +01:00
CNTK_202_Language_Understanding.ipynb	Add a default (true) for the unit-gain flag value	2017-01-20 09:27:36 +01:00
CNTK_203_Reinforcement_Learning_Basics.ipynb	CNTK_203_Reinforcement_Learning_Basics_test.py: bump timeout	2017-01-19 13:51:43 +01:00
CNTK_204_Sequence_To_Sequence.ipynb	Add a default (true) for the unit-gain flag value	2017-01-20 09:27:36 +01:00
CNTK_205_Artistic_Style_Transfer.ipynb	Make Jupyter Notebook tests device-aware	2017-01-12 13:59:56 +01:00
README.md	Addressed CR comments	2016-11-14 16:24:52 +01:00

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)