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Setup CNTK on your machine
Microsoft Cognitive Toolkit (CNTK) is easy to install.
On Windows, if you have configured Anaconda3 Python 3.5 as your active Python environment, run this command to install the CNTK CPU-only version:
pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.0.rc1-cp35-cp35m-win_amd64.whl
On Ubuntu 16.04, if you have configured Anaconda3 Python 3.5 as your active Python environment, run these commands to install the CNTK CPU-only version:
sudo apt-get install openmpi-bin
pip install https://cntk.ai/PythonWheel/CPU-Only/cntk-2.0.rc1-cp35-cp35m-linux_x86_64.whl
You can easily fine tune your PIP installation, including information about configuring information and the easy installation of tutorials, sample and Jupyter notebooks. For Windows, check out this page, for Linux this one.
For all the other ways to install CNTK or setup the CNTK development environment, see the links to the install options below.
The Microsoft Cognitive Toolkit (CNTK) supports both 64-bit Windows and 64-bit Linux platforms.
You can install the complete source code of CNTK and build the binaries on your machine, but we also provide regular binary drops of the CNTK executables, including sample data and sample models.
If you just want to download and install the latest precompiled binaries to your machine, follow the instructions here:
| Windows | Linux |
|---|---|
| Python-only installation | Python-only installation |
| Script-driven installation | Script-driven installation |
| Manual installation | Manual installation |
| Docker installation |
If you want to take a look at the CNTK source code, compile CNTK yourself, make changes to the CNTK codebase, and contribute these changes back to the community, these are the pages for you:
| Windows | Linux |
|---|---|
| Script-driven development setup | |
| Manual development Setup | Manual Development Environment Setup |
| Migration from VS13 to VS15 |
You may use CNTK via Microsoft Azure Virtual Machine offering (Windows and Linux) or install it as a Docker container (Linux). See the corresponding sections:
If you want to learn more about CNTK usage and how to execute the provided samples, you find more information on the following pages