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  2. Comparison of deep learning software - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_deep...

    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 ...

  3. List of programming languages for artificial intelligence

    en.wikipedia.org/wiki/List_of_programming...

    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.

  4. Neural Engineering Object - Wikipedia

    en.wikipedia.org/wiki/Neural_Engineering_Object

    Neural Engineering Object (Nengo) is a graphical and scripting software for simulating large-scale neural systems. [1] As the neural network software Nengo is a tool for modelling neural networks with applications in cognitive science , psychology , artificial intelligence and neuroscience .

  5. Apache MXNet - Wikipedia

    en.wikipedia.org/wiki/Apache_MXNet

    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).

  6. Neural network software - Wikipedia

    en.wikipedia.org/wiki/Neural_network_software

    SNNS research neural network simulator. Historically, the most common type of neural network software was intended for researching neural network structures and algorithms. The primary purpose of this type of software is, through simulation, to gain a better understanding of the behavior and the properties of neural network

  7. SqueezeNet - Wikipedia

    en.wikipedia.org/wiki/SqueezeNet

    SqueezeNet is a deep neural network for image classification released in 2016. SqueezeNet was developed by researchers at DeepScale, University of California, Berkeley, and Stanford University. In designing SqueezeNet, the authors' goal was to create a smaller neural network with fewer parameters while achieving competitive accuracy.

  8. Surrogate model - Wikipedia

    en.wikipedia.org/wiki/Surrogate_model

    Download as PDF; Printable version; ... space mapping; [2] artificial neural networks and Bayesian networks. [3] ... Matlab SUrrogate MOdeling ToolboxMatlab SUMO ...

  9. Time delay neural network - Wikipedia

    en.wikipedia.org/wiki/Time_delay_neural_network

    Matlab: The neural network toolbox has explicit functionality designed to produce a time delay neural network give the step size of time delays and an optional training function. The default training algorithm is a Supervised Learning back-propagation algorithm that updates filter weights based on the Levenberg-Marquardt optimizations.