simple perceptrons
[/ˈsɪmpəl pərˈsɛptrɑnz/]
nounpl: simple perceptrons
perceptrons simples
1. Basic machine learning algorithms that classify inputs into two categories using a linear decision boundary; fundamental artificial neural networks with a single layer
Simple perceptrons are often used as introductory models in machine learning courses.
Perceptrons simples são frequentemente usados como modelos introdutórios em cursos de aprendizado de máquina.
2. Early form of artificial neural networks consisting of input nodes, weights, and an output node that makes binary classifications
The simple perceptron was developed by Frank Rosenblatt in 1958.
O perceptron simples foi desenvolvido por Frank Rosenblatt em 1958.
This is a technical term primarily used in computer science, artificial intelligence, and machine learning contexts in both Brazil and the USA. It represents a foundational concept in the history of neural networks and is commonly taught in universities and online coding bootcamps. The term is used identically in both English-speaking and Portuguese-speaking technical communities, though Brazilian Portuguese uses 'perceptrons simples' while European Portuguese may alternate between pluralization forms.
Related Idioms & Phrases
train a simple perceptron
linear separability of simple perceptrons
limitations of simple perceptrons
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