CognitiveToolkit – CNTK on Microsoft Azure


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The Microsoft Cognitive Toolkit—previously known as CNTK—empowers you to harness the intelligence within massive datasets through deep learning by providing uncompromised scaling, speed and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms you already use. Hear about the team that developed the Cognitive Toolkit. and http://www.microsoft.com/en-us/research/product/cognitive-toolkit/ 

CNTK is available as Microsoft Azure Virtual Machine offerings. Currently CPU-only configurations are provided. Use the links below to set up the machines and get additional information.

We currently have CNTK installed on a Windows Virtual Machine
And a Linux Virtual Machines

The Microsoft Cognitive Toolkit – CNTK – is a unified deep-learning toolkit by Microsoft Research.

It can be included as a library in your Python or C++ programs, or used as a standalone machine learning tool through its own model describtion language (BrainScript).

CNTK supports 64-bit Linux or 64-bit Windows operating systems. To install you can either choose pre-compiled binary packages, or compile the Toolkit from the source provided in Github.

Here are a few pages to get started:

Note to search the pages of this Wiki, in the search box, type: Language:Markdown yourSearchText

This Wiki is the most up-to-date information about the Microsoft Cognitive Toolkit. For more background refer to the tutorials provided. A general introduction to computational networks and the core algorithms in CNTK, or to cite the work, please refer to the Microsoft Technical Report MSR-TR-2014-112: “An Introduction to Computational Networks and the Computational Network Toolkit”. The source of this report is in the Git repository folder.
It is updated less frequently and shouldn’t be used the most up-to-date source of information.

We also have a dedicated Github Repo for the CNTK toollkit at https://github.com/Microsoft/CNTK/

But here are some quick link Resources

Getting Started

Additional Documentation

How to use CNTK

Using CNTK Models in Your Code

Advanced topics

Licenses

Source Code & Development

Comments (1)

  1. Lee Stott says:

    Sample CNTK Jupyter Notebooks
    CNTK_101_LogisticRegression.ipynb in Python 3.x
    CNTK_102_FeedForward.ipynb in Python 3.x
    CNTK_103A_MNIST_DataLoader.ipynb in Python 3.x
    CNTK_103B_MNIST_FeedForwardNetwork.ipynb in Python 3.x
    CNTK_202_Language_Understanding.ipynb in Python 3.x
    CNTK_203_Reinforcement_Learning_Basics.ipynb in Python 3.x
    CNTK_204_Sequence_To_Sequence.ipynb in conda-env-cntk-py

    Available at Notebooks.azure.com – https://notebooks.azure.com/library/jmB6HXB9WDc/dashboard?page=1