The Microsoft Cognitive Toolkit - aka CNTK

A quick introduction to Microsoft Cognitive Toolkit



The Microsoft Cognitive Toolkit (https://www.microsoft.com/en-us/research/product/cognitive-toolkit/), is a unified deep-learning toolkit that describes neural networks as a series of computational steps via a directed graph. In this directed graph, leaf nodes represent input values or network parameters, while other nodes represent matrix operations upon their inputs. CNTK allows to easily realize and combine popular model types such as feed-forward DNNs, convolutional nets (CNNs), and recurrent networks (RNNs/LSTMs). It implements stochastic gradient descent (SGD, error backpropagation) learning with automatic differentiation and parallelization across multiple GPUs and servers. CNTK has been available under an open-source license since April 2015. It is our hope that the community will take advantage of CNTK to share ideas more quickly through the exchange of open source working code.



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.https://github.com/Microsoft/CNTK/wiki

Examples here:
https://www.microsoft.com/en-us/research/product/cognitive-toolkit/model-gallery/

Use for instance in object detection in video (http://image-net.org/challenges/LSVRC/2015/), Speech recognition (https://github.com/Microsoft/CNTK/tree/master/Examples/Speech/AN4), Feed Forward classification, finance timeseries,