文件列表:

LICENSE (1035, 2016-08-02)
config (0, 2016-08-02)
config\setup_tools_for_linux_dsvm.sh (4850, 2016-08-02)
install.sh (594, 2016-08-02)
solutions (0, 2016-08-02)
solutions\character_recognition (0, 2016-08-02)
solutions\character_recognition\R (0, 2016-08-02)
solutions\character_recognition\R\mxnet (0, 2016-08-02)
solutions\character_recognition\R\mxnet\fully_connected.R (2055, 2016-08-02)
solutions\character_recognition\R\mxnet\lenet.R (2583, 2016-08-02)
solutions\character_recognition\data (0, 2016-08-02)
solutions\character_recognition\data\download_mnist_data.sh (196, 2016-08-02)
solutions\general_examples (0, 2016-08-02)
solutions\general_examples\R (0, 2016-08-02)
solutions\general_examples\R\mxnet (0, 2016-08-02)
solutions\general_examples\R\mxnet\basic_nn_classification.R (1136, 2016-08-02)
solutions\general_examples\R\mxnet\basic_nn_regression.R (1089, 2016-08-02)

# Deep Learning tools for the Data Science Virtual Machine This repo will help you to leverage deep learning applications using the Microsoft's [Data Science Virtual Machine](https://azure.microsoft.com/en-gb/documentation/articles/machine-learning-data-science-linux-dsvm-intro/) (DSVM). It contains two kinds of resources: installation scripts to easily configure the best deep learning libraries in your DSVM and solution packages to let you start with deep learning applications. ## Deep Learning Libraries The following libraries are installed via a simple script: * [CNTK](https://www.cntk.ai/): Microsoft's native library for deep learning (already preinstalled in the DSVM). Code in C# and C++. * [mxnet](https://github.com/dmlc/mxnet): Distributed library for deep learning. Code in R, python, C++ and Scala. * [keras](https://github.com/fchollet/keras): Popular deep learning library. Code in python. * [caffe](https://github.com/BVLC/caffe): Deep learning library from Berkeley. Code in C++. * [torch](https://github.com/torch/torch7): Mathematical framework for deep learning. Code in Lua and C. * [chainer](https://github.com/pfnet/chainer): Deep learning library based in caffe. Code in python. * [theano](https://github.com/Theano/Theano): Mathematical framework for deep learning. Code in python To install them all, just log in in your DSVM (in Linux) and write: sudo chmod +x -R install.sh config ./install.sh ## Solutions Next there are several solutions that will help you learn and understand deep learning. * Character Recognition * Image classification CIFAR * Image classification ImageNet * Implementation of artistic style in images * Word prediction from characters * Sentiment Analisys * General machine learning examples

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