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MATLAB + Deep Learning Toolbox (formally Neural Network Toolbox) MathWorks: 1992 Proprietary: No Linux, macOS, Windows: C, C++, Java, MATLAB: MATLAB: No No Train with Parallel Computing Toolbox and generate CUDA code with GPU Coder [23] No Yes [24] Yes [25] [26] Yes [25] Yes [25] Yes With Parallel Computing Toolbox [27] Yes Microsoft Cognitive ...
MATLAB has many toolboxes specifically for the development of AI including the Statistics and Machine Learning Toolbox and Deep Learning Toolbox. These toolboxes provide APIs for the high-level and low-level implementation and use of many types of machine learning models that can integrate with the rest of the MATLAB ecosystem.
This original version of SqueezeNet was implemented on top of the Caffe deep learning software framework. Shortly thereafter, the open-source research community ported SqueezeNet to a number of other deep learning frameworks. On February 26, 2016, Eddie Bell released a port of SqueezeNet for the Chainer deep learning framework. [3]
Apache MXNet is an open-source deep learning software framework that trains and deploys deep neural networks. It aims to be scalable, allows fast model training, and supports a flexible programming model and multiple programming languages (including C++, Python, Java, Julia, MATLAB, JavaScript, Go, R, Scala, Perl, and Wolfram Language).
Shogun, an open-source large-scale machine-learning toolbox that provides several SVM implementations (like libSVM, SVMlight) under a common framework and interfaces to Octave, MATLAB, Python, R; Waffles is a free-software collection of command-line tools designed for scripting machine-learning operations in automated experiments and processes.
OpenNN (Open Neural Networks Library) is a software library written in the C++ programming language which implements neural networks, a main area of deep learning research. [1] The library is open-source , licensed under the GNU Lesser General Public License .
Caffe supports many different types of deep learning architectures geared towards image classification and image segmentation. It supports CNN, RCNN, LSTM and fully-connected neural network designs. [8] Caffe supports GPU- and CPU-based acceleration computational kernel libraries such as Nvidia cuDNN and Intel MKL. [9] [10]
Microsoft Cognitive Toolkit, [3] previously known as CNTK and sometimes styled as The Microsoft Cognitive Toolkit, is a deprecated [4] deep learning framework developed by Microsoft Research. Microsoft Cognitive Toolkit describes neural networks as a series of computational steps via a directed graph .