1. A machine learning approach where algorithms are trained on labeled datasets, where each training example has an associated correct answer or target output, enabling the model to learn mappings between inputs and outputs.
Supervised machine learning is used to build email spam filters by training on examples of spam and legitimate emails.
O aprendizado de máquina supervisionado é usado para construir filtros de spam de email treinando em exemplos de emails de spam e legítimos.
2. A category of machine learning techniques that rely on labeled training data to make predictions or classifications on new, unseen data.
In supervised machine learning, the model learns the relationship between features and labels during the training phase.
No aprendizado de máquina supervisionado, o modelo aprende a relação entre características e rótulos durante a fase de treinamento.