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The Microsoft Cognitive Toolkit

A framework for building deep learning models using computational graphs

&

+ScalabilityScales seamlessly from CPUs to GPUs to clusters, handling massive datasets with ease.
+Python/C++ API SupportIncludes Python/C++ API support offering flexibility and developer choice
+TutorialsOnboard quickly with Python notebooks and examples.
+Layers InterfaceAn easy-to-use interface for building neural networks.
+Custom Layer SupportAllows users to define their custom layers for specific tasks, extending its functionality
+Sequence-to-Sequence with AttentionSupports sequence-to-sequence models with attention mechanisms
+Batch NormalizationBuilt-in batch normalization for improved training stability.
+Convolutional Neural Networks (CNN)Powerful for image recognition and classification.
+Feedforward Neural Networks (FFN)Efficiently processes dense data.
+Recurrent Neural Networks (RNN)Handles sequential data like speech and text.
+BrainScript SupportHandles multi-dimensional sparse and dense data.
+Automatic DifferentiationAutomatically computes gradients, a critical step in training neural networks
+Built-in Data ReadersBuilt-in data readers optimized for various formats’ data loading and parsing

Platform

Social

 

System Requirements

Version ↓
#Recommended
1
Ubuntu 16.04 LTS (64 bit)
2
GNU C++ 5.4.0
3
Open MPI v. 1.10.7
4
Intel® MKLML library
5
  • NVIDIA CUDA 9.0
  • NVIDIA cuDNN 7.0 for CUDA 9.0
  • NVIDIA CUB 1.7.4
6
OpenCV v.3.1.0
7
zlib v.1.2.8
8
libzip v.1.1.2
9
OpenJDK 7, 64-bit
10
Anaconda3 4.1.1 (64 bit)
11
The presented set of product versions is not restrictive, i.e. CNTK may work well in many other configurations
#Recommended
1
  • Windows 8.1 Pro (64 bit)
  • Windows 10 (64 bit)
  • Windows Server 2012 R2 Standard and later
2
Visual Studio Enterprise 2017
3
Microsoft MPI v. 7.0
4
Intel® MKLML library
5
  • NVIDIA CUDA 9.0
  • NVIDIA cuDNN 7.0 for CUDA 9.0
  • NVIDIA CUB 1.7.4
6
OpenCV v.3.1.0
7
zlib v.1.2.8
8
libzip v.1.1.3
9
Java SE Development Kit 8 v1.8.0_131, 64-bit
10
Anaconda3 4.1.1 (64 bit)
11
The presented set of product versions is not restrictive, i.e. CNTK may work well in many other configurations

Ratings

4.90
5

Capterra
5.0
5
based on 5 reviews
G2CROWD
4.8
5
based on 4 reviews

Written in

C++, Jupyter Notebook, Python

Initial Release

26 January 2016