Information about Test

  1. Convolutional neural network

    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

    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

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

  4. Transformer (machine learning model)

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

  5. Language model

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

  6. Encog

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

  7. Artificial intelligence

    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)

  8. Neural network software

    Neural network software is used to simulate, research, develop, and apply artificial neural networks, software concepts adapted from biological neural

  9. History of artificial neural networks

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

  10. Speech recognition

    related recurrent neural networks (RNNs) and Time Delay Neural Networks(TDNN's) have demonstrated improved performance in this area. Deep Neural Networks and