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2017-02-01. V 2.0 Beta 10 Release Highlights of this Release:
- New and updated core and Python API features.
- New Tutorials and Examples:
- A Python version of the deconvolution layer and image auto encoder example was added (Example 07_Deconvolution in Image - Getting Started).
- A Python distributed training example for image classification using AlexNet was added, cf. here
- Basic implementation of Generative Adversarial Networks (GAN) networks
- Training with Sampled Softmax
- New CNTK NuGet Packages.
See more in the Release Notes. Get the Release from the CNTK Releases page.
2017-01-25. V 2.0 Beta 9 Release available at Docker Hub
CNTK V 2.0 Beta 9 Runtime packages are now available as Public Images at Docker Hub.
See more on CNTK as Docker Images in this Wiki article.
2017-01-25. 1bit-SGD Code is relocated to GitHub. Submodule configuration update is required for affected users
This news is related to users who are working with CNTK code base. If you use Binary or Docker Runtime Images installation you may ignore it.
Effective January 25, 2017 CNTK 1-bit Stochastic Gradient Descent (1bit-SGD) and BlockMomentumSGD code is moved to a new Repository in GitHub.
If you cloned CNTK Repository with 1bit-SGD enabled prior to January 25, 2017 you need to update git submodule configuration as described in this Wiki article.
2017-01-20. V 2.0 Beta 9 Release
Highlights of this Release:
- Default Python version is now 3.5 (relates to default parameters in client installations as well as Runtime Images at Docker Hub).
- New and updated core and Python API features.
- New Tutorials and Examples:
- Deconvolution layer and image auto encoder example using deconvolution and unpooling (Example 07_Deconvolution in Image - Getting Started).
- Basic autoencoder with MNIST data.
- LSTM Timeseries with Simulated Data (Part A). (More will come in the next Releases)
- New CNTK NuGet Packages.
See more in the Release Notes.
Get the Release from the CNTK Releases page.
2017-01-19. V 2.0 Beta 8 Release available at Docker Hub
CNTK V 2.0 Beta 8 Runtime packages are now available as Public Images at Docker Hub.
See more on CNTK as Docker Images in this Wiki article.
2017-01-16. V 2.0 Beta 8 Release
Highlights of this Release:
- Support of Python v. 2.7, 3.4, and 3.5. See binary and source setup instructions to find out about how to select Python version.
- New Python API features.
- New Python example Feature extraction using a trained model in Python API.
- Support of Visual Studio 2015 for Windows version.
- Introduction of C# API in CNTK Evaluation Library and a new set of CNTK NuGet Packages.
- CNTK Runtime packages are now available as Public Images at Docker Hub. (Beta 7 is currently available; Beta 8 Images availability will be announced separately in a few days)
- Version 3 of CNTK Custom MKL Library is available.
See more in the Release Notes.
Get the Release from the CNTK Releases page.
2017-01-10. CNTK for Windows supports Visual 2015
If you pull or merge the master branch, CNTK will now require Visual Studio 2015 to build on Windows. There are two ways to move your development environment to Visual Studio 2015:
- Migrate VS2013 to VS2015: This gives you a fine grained control over where components are installed
- Script driven setup: This gives you an mostly automated migration to Visual Studio 2015