multilayer perceptrons
Multilayer perceptrons (MLPs) are artificial neural networks composed of multiple layers of interconnected nodes (neurons). Each layer processes and transforms the input data before passing it to the next layer. MLPs are particularly efficient in solving complex problems such as pattern recognition and classification due to their ability to learn and model nonlinear relationships.
Requires login.
Related Concepts (1)
Similar Concepts
- artificial neural networks
- convolutional layers
- convolutional neural networks
- convolutional neural networks (cnn)
- feedforward neural networks
- fuzzy neural networks
- machine learning for perception
- multilayer perceptron
- neural network architecture
- neural network architectures
- neural network layers
- neural network models
- neural network training
- neural networks
- recurrent neural networks