multi-layer perceptrons
[ˈmʌl.ti ˈleɪ.ər pərˈsɛp.ʃənz]
nounpl: multi-layer perceptrons
perceptrons multicamadas
1. A type of artificial neural network composed of multiple layers of interconnected nodes (neurons) that process information through weighted connections and activation functions, used for supervised learning tasks
Multi-layer perceptrons are widely used in deep learning for image recognition and natural language processing tasks.
Perceptrons multicamadas são amplamente utilizados em aprendizado profundo para tarefas de reconhecimento de imagens e processamento de linguagem natural.
2. A feedforward neural network with one or more hidden layers between input and output layers, capable of learning non-linear relationships in data
The multi-layer perceptron architecture includes an input layer, one or more hidden layers, and an output layer.
A arquitetura do perceptron multicamadas inclui uma camada de entrada, uma ou mais camadas ocultas e uma camada de saída.
Multi-layer perceptrons are fundamental to modern artificial intelligence and are taught extensively in Brazilian and Portuguese universities' computer science and engineering programs. The term is primarily used in technical, academic, and professional AI/ML contexts rather than in casual conversation. This represents the core architecture that enabled the recent explosion in deep learning applications globally.
Related Idioms & Phrases
training a multi-layer perceptron
backpropagation through multi-layer perceptrons
universal approximation theorem (related to MLPs)
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