fully connected layers
Fully connected layers, also known as dense layers, are a type of artificial neural network layer in which each neuron is connected to every neuron in the previous layer. In other words, all the neurons in a fully connected layer receive input from all the neurons in the previous layer.
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Related Concepts (21)
- activation functions
- artificial neural networks
- autoencoders
- backpropagation
- connectionist models
- convolutional neural networks
- deep learning
- dropout regularization
- feedforward neural networks
- gradient descent
- hyperparameter tuning
- loss functions
- multilayer perceptrons
- neural network layers
- optimization algorithms
- overfitting
- recurrent neural networks
- regularization techniques
- supervised learning
- unsupervised learning
- weight initialization