The Microsoft Cognitive Toolkit
The Microsoft Cognitive Toolkit is a deep learning framework developed by Microsoft Research, previously known as CNTK
Features
The Microsoft Cognitive Toolkit—previously known as CNTK—is an open-source toolkit for commercial-grade distributed deep learning. It describes neural networks as a series of computational steps via a directed graph.
The Microsoft Cognitive Toolkit enables to leverage the information within massive data-sets through deep learning by providing scaling, speed, and accuracy with commercial-grade quality and compatibility with the programming languages and algorithms already in use.
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System Requirements
| # | Recommended |
|---|---|
| 1 | OS: Ubuntu 16.04 LTS (64 bit) |
| 2 | Compiler: GNU C++ 5.4.0 |
| 3 | MPI: Open MPI v. 1.10.7 |
| 4 | Math Library: Intel® MKLML library |
| 5 | NVIDIA Components: NVIDIA CUDA 9.0, NVIDIA cuDNN 7.0 for CUDA 9.0, NVIDIA CUB 1.7.4 |
| 6 | OpenCV: OpenCV v.3.1.0 |
| 7 | zlib Library: zlib v.1.2.8 |
| 8 | libzip Library: libzip v.1.1.2 |
| 9 | Java: OpenJDK 7, 64-bit |
| 10 | Anaconda Python: Anaconda3 4.1.1 (64 bit) |
| # | Recommended |
|---|---|
| 1 | OS: Windows 8.1 Pro (64 bit), Windows 10 (64 bit), Windows Server 2012 R2 Standard and later |
| 2 | Compiler: Visual Studio Enterprise 2017 |
| 3 | MPI: Microsoft MPI v. 7.0 |
| 4 | Math Library: Intel® MKLML library |
| 5 | NVIDIA Components: NVIDIA CUDA 9.0, NVIDIA cuDNN 7.0 for CUDA 9.0, NVIDIA CUB 1.7.4 |
| 6 | OpenCV: OpenCV v.3.1.0 |
| 7 | zlib Library: zlib v.1.2.8 |
| 8 | libzip Library: libzip v.1.1.3 |
| 9 | Java: Java SE Development Kit 8 v1.8.0_131, 64-bit |
| 10 | Anaconda Python: Anaconda3 4.1.1 (64 bit) |
Developer
Microsoft Research
Written in
C++, Jupyter Notebook, Python
Initial Release
26 January 2016
Alternatives
Artificial Intelligence
Accord.NET
AForge.NET
Eclipse Deeplearning4j
OpenCog
TensorFlow
Machine Learning
Apache Mahout
Apache MXNet (Incubating)
Apache Spark
Apache SystemML
Eclipse Deeplearning4j
MALLET
Massive Online Analysis (MOA)
mlpack
OpenCV
Orange
PyTorch
scikit-learn
TensorFlow
Torch
Weka
Yooreeka
Deep Learning
Apache MXNet (Incubating)
Apache SystemML
Caffe
Eclipse Deeplearning4j
OpenNN
PyTorch
TensorFlow
Torch
Weka
Notes
- In System Requirements, the presented set of product versions is not restrictive, i.e. CNTK may work well in many other configurations.
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