Information about Test

  1. Recurrent neural network

    A recurrent neural network (RNN) is a class of artificial neural networks where connections between nodes form a directed graph along a temporal sequence

  2. Bidirectional recurrent neural networks

    Bidirectional Recurrent Neural Networks (BRNN) connect two hidden layers of opposite directions to the same output. With this form of generative deep

  3. Feedforward neural network

    feedforward neural network is an artificial neural network wherein connections between the nodes do not form a cycle. As such, it is different from recurrent neural

  4. Artificial neural network

    Artificial neural networks (ANN) or connectionist systems are computing systems that are inspired by, but not identical to, biological neural networks that

  5. 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

  6. Types of artificial neural networks

    types of artificial neural networks (ANN). Artificial neural networks are computational models inspired by biological neural networks, and are used to approximate

  7. Long short-term memory

    an artificial recurrent neural network (RNN) architecture used in the field of deep learning. Unlike standard feedforward neural networks, LSTM has feedback

  8. Deep learning

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

  9. Recursive neural network

    A recursive neural network is a kind of deep neural network created by applying the same set of weights recursively over a structured input, to produce

  10. 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