Revision e61c2c99b430241a064a1cfed26daf533e40cfcf authored by Reza Farrahi M on 10 July 2017, 15:09:47 UTC, committed by GitHub on 10 July 2017, 15:09:47 UTC
It is the 2nd instance.
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README.md
# Tutorials
In this folder you 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 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.
### 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](https://docs.microsoft.com/en-us/cognitive-toolkit/Tutorials).
* Hello World - Logistic Regression ([Details](https://docs.microsoft.com/en-us/cognitive-toolkit/Tutorials))
* Image Hands On ([Details](https://docs.microsoft.com/en-us/cognitive-toolkit/Hands-On-Labs-Image-Recognition))
* SLU (Language Understanding) Hands On ([Details](https://docs.microsoft.com/en-us/cognitive-toolkit/Hands-On-Labs-Language-Understanding))
* Object detection using Fast R-CNN ([Code](https://github.com/Microsoft/CNTK/tree/master/Examples/Image/Detection/FastRCNN), [Details](https://docs.microsoft.com/en-us/cognitive-toolkit/Object-Detection-using-Fast-R-CNN))
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