이 과정은 Transformer 아키텍처와 BERT(Bidirectional Encoder Representations from Transformers) 모델을 소개합니다. 셀프 어텐션 메커니즘 같은 Transformer 아키텍처의 주요 구성요소와 이 아키텍처가 BERT 모델 빌드에 사용되는 방식에 관해 알아봅니다. 또한 텍스트 분류, 질문 답변, 자연어 추론과 같이 BERT를 활용할 수 있는 다양한 작업에 대해서도 알아봅니다. 이 과정은 완료하는 데 대략 45분이 소요됩니다.
Transformer Models and BERT Model - 한국어
Gain insight into a topic and learn the fundamentals.
Advanced level
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1 hour to complete
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What you'll learn
Transformer 아키텍처의 주요 구성요소를 이해합니다
Transformer를 사용한 BERT 모델 빌드 방식을 알아봅니다
BERT를 사용하여 다양한 자연어 처리(NLP) 작업을 해결합니다
Details to know
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Assessments
1 assignment
Taught in Korean
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There is 1 module in this course
이 모듈에서는 셀프 어텐션 메커니즘 같은 Transformer 아키텍처의 주요 구성요소와 이 아키텍처가 BERT 모델 빌드에 사용되는 방식에 대해 알아봅니다. 또한 텍스트 분류, 질문 답변, 자연어 추론과 같이 BERT를 활용할 수 있는 다양한 작업에 대해서도 알아봅니다.
What's included
2 videos1 reading1 assignment
Instructor
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Princeton University
Macquarie University
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