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[link] Microsoft releases CNTK, deep learning toolkit, on GITHUB

Posted 26 January 2016 - 03:53 PM

Well hells bells - isn't that spiffy! I wonder if I have any spare GPUs I can burn out processing all the tutorials and topics in DIC?? Ha!

http://blogs.microso...lkit-on-github/
https://github.com/Microsoft/CNTK
http://www.cntk.ai/
https://github.com/Microsoft/CNTK/wiki

Quote

Over the past few years, the field of deep learning has exploded as more researchers have started running machine learning algorithms using deep neural networks, which are systems that are inspired by the biological processes of the human brain. Many researchers see deep learning as a very promising approach for making artificial intelligence better.

Those gains have allowed researchers to create systems that can accurately recognize and even translate conversations, as well as ones that can recognize images and even answer questions about them.

Internally, Microsoft is using CNTK on a set of powerful computers that use graphics processing units, or GPUs.

[...]
Chris Basoglu, a principal development manager at Microsoft who also worked on the toolkit, said one of the advantages of CNTK is that it can be used by anyone from a researcher on a limited budget, with a single computer, to someone who has the ability to create their own large cluster of GPU-based computers.



Quote

CNTK, the Computational Network Toolkit by Microsoft Research, 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


.. looks like it may be using CUDA.
https://developer.nv...om/cuda-toolkit

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