Information about Test

  1. Convolutional neural network

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    In deep learning, a convolutional neural network (CNN, or ConvNet) is a class of deep neural networks, most commonly applied to analyzing visual imagery

  2. Neural network

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    A neural network is a network or circuit of neurons, or in a modern sense, an artificial neural network, composed of artificial neurons or nodes. Thus

  3. Deep learning

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    such as deep neural networks, deep belief networks, recurrent neural networks and convolutional neural networks have been applied to fields including computer

  4. Artificial intelligence

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    the program that beat a top Go champion in 2016. Early on, deep learning was also applied to sequence learning with recurrent neural networks (RNNs)

  5. Encog

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    Counterpropagation Neural Network (CPN) Elman Recurrent Neural Network Neuroevolution of augmenting topologies (NEAT) Feedforward Neural Network (Perceptron)

  6. Language model

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    models and recurrent neural network models MITLM – MIT Language Modeling toolkit. Free software NPLM – Free toolkit for feedforward neural language models

  7. Generative adversarial network

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    adversarial network (GAN) is a class of machine learning systems invented by Ian Goodfellow and his colleagues in 2014. Two neural networks contest with

  8. Machine learning in video games

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    has made it a commonly used tool for deep learning in games. Recurrent neural networks are a type of ANN that are designed to process sequences of data

  9. Transformer (machine learning model)

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    primarily in the field of natural language processing (NLP). Like recurrent neural networks (RNNs), Transformers are designed to handle ordered sequences

  10. History of artificial neural networks

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    many-layered feedforward neural networks. Between 2009 and 2012, recurrent neural networks and deep feedforward neural networks developed in Schmidhuber's

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