Recurrent Neural Networks(RNN) 순환 신경망

2022. 9. 7. 11:37AI/인공지능 공부

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RNN 참고 문서
Neural Network와 마찬가지로 IBM에서 제공한 위 문서를 참고했다.

RNN

Learn how recurrent neural networks use sequential data to solve common temporal problems seen in language translation and speech recognition.

 

1. RNN이란?

  • a type of artificial neural network which uses sequential data or time series data.
    • commonly used for ordinal or temporal problems
      1. language translation
      2. natural language processing (nlp)
      3. speech recognition
      4. image captioning
  • distinguished by their “memory” as they take information from prior inputs to influence the current input and output.
    • traditional deep neural networks: inputs and outputs are independent of each other
    • recurrent neural networks: outputs depend on the prior elements within the sequence
  • While future events would also be helpful in determining the output of a given sequence, unidirectional recurrent neural networks cannot account for these events in their predictions.

각 요소를 판단할 때 이전 요소에 대한 정보가 들어와서 판단하는 데 영향을 주는 것이다.


아래는 RNN의 개념을 이해하는 데 도움이 된 영상 링크이다.

https://www.youtube.com/watch?v=oORGMrhsx0o 

https://www.youtube.com/watch?v=PahF2hZM6cs 

 

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