Coursera
MOOC / Non-credit
0
Transformer Models and BERT Model - 한국어
About this course
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.
D
48/100
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- Who stands behind it
- 20/35
- How complete the listing is
- 12/20
Scores how much the provider publishes and who stands behind it — not how well it is taught.
What you'll learn
- understanding of Transformer architecture
- knowledge of the BERT model
- ability to apply BERT to text classification tasks
- insight into using BERT for question answering and natural language inference
Artificial Intelligence
#deep learning
#artificial intelligence
#machine learning
#nlp
#natural language processing
#text classification
#question answering
#bert
#transformer models
#self-attention
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