Samples in Visual Studio solution format are provided for users to get started with deep learning using: Deep House is a more lucrative subgenre of house after a while DJ's started exploring more ways to make house sound more advanced, the experiments made the breakthrough and we got some differences like, softer basslines, heavily used vocal samples, intensive melodies created with modular effects like reverbs and delays.
Each solution has one or more sample projects.Solutions are separated by different deep learning frameworks they use:
1. PrerequisitesUsing a one-click installer to setup deep learning frameworks has been moved to here, please visit it for details. 2. Download Data![]() 3. Run SamplesThis project welcomes contributions and suggestions. Most contributions require you toagree to a Contributor License Agreement (CLA) declaring that you have the right to,and actually do, grant us the rights to use your contribution. For details, visithttps://cla.microsoft.com. When you submit a pull request, a CLA-bot will automatically determine whether you needto provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow theinstructions provided by the bot. You will only need to do this once across all repositories using our CLA. This project has adopted the Microsoft Open Source Code of Conduct.For more information see the Code of Conduct FAQor contact [email protected] with any additional questions or comments. Most of the samples scripts are from official github of each framework. They are under different licenses. The scripts of CNTK are under MIT license. The scripts of Tensorflow samples are under Apache 2.0 license.There are no changes to the original code. For the scripts of Caffe2, different versions released with different licenses.Currently, the master branch is under Apache 2.0 license. But the version 0.7 and 0.8.1 were released with BSD 2-Clause license.The scripts in our solution are based on caffe2 GitHub source tree version 0.7 and 0.8.1, with BSD 2-Clause license. The scripts of Keras are under MIT license. The scripts of Theano are under BSD license. The scripts of MXNet are under Apache 2.0 license.There are no changes to the original code. ![]() The scripts of Chainer are under MIT license.
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