representation learning
[/ˌrɛprɪˈzɛnˈteɪʃən ˈlɜrnɪŋ/]
noun
aprendizado de representação
1. A machine learning approach that automatically discovers the representations needed for feature detection or classification from raw input
Representation learning enables neural networks to learn effective features without manual feature engineering.
O aprendizado de representação permite que redes neurais aprendam características efetivas sem engenharia manual de recursos.
2. The process of learning to encode information in a form suitable for processing by machine learning algorithms
Deep learning is a subset of representation learning that uses multiple layers to learn hierarchical representations.
O aprendizado profundo é um subconjunto do aprendizado de representação que usa múltiplas camadas para aprender representações hierárquicas.
This is a specialized technical term predominantly used in artificial intelligence and machine learning communities globally. In Brazil, it's primarily used in academic research, tech companies, and AI-focused startups in major cities like São Paulo and Rio de Janeiro. The English term is often used directly in Portuguese technical documentation, though 'aprendizado de representação' is the standard Portuguese equivalent increasingly adopted in Brazilian AI research.
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