딥 러닝 전문화의 다섯 번째 과정에서는 시퀀스 모델과 음성 인식, 음악 합성, 챗봇, 기계 번역, 자연어 처리(NLP) 등과 같은 흥미로운 애플리케이션에 익숙해질 것입니다.
시퀀스 모델
Gain insight into a topic and learn the fundamentals.
Intermediate level
Recommended experience
40 hours to complete
3 weeks at 13 hours a week
Flexible schedule
Learn at your own pace
Skills you'll gain
Details to know
Shareable certificate
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Assessments
4 assignments
Taught in Korean
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There are 4 modules in this course
LSTM, GRU 및 양방향 RNN을 포함하여 시계열 데이터에 뛰어난 성능을 보이는 모델 유형 및 여러 변형 및 순환 신경망 확인.
What's included
12 videos4 readings1 assignment3 programming assignments2 app items
자연어 처리의 딥 러닝는 가장 강력한 조합입니다. 단어 벡터 표현 및 임베딩 레이어를 사용하여 감정 분석, 명명된 엔터티 인식 및 신경망 기계 번역을 비롯한 다양한 애플리케이션에서 뛰어난 성능으로 순환 신경망을 훈련합니다.
What's included
10 videos1 reading1 assignment2 programming assignments1 app item
입력 시퀀스가 주어졌을 때 모델이 주의를 집중할 위치를 결정하는 데 도움이 되는 알고리즘인 주의 메커니즘을 사용하여 시퀀스 모델을 보강합니다. 그런 다음 음성 인식과 오디오 데이터를 처리하는 방법을 살펴봅니다.
What's included
10 videos3 readings1 assignment2 programming assignments1 app item
What's included
5 videos4 readings1 assignment1 programming assignment1 app item3 ungraded labs
Offered by
Recommended if you're interested in Machine Learning
University of Virginia Darden School Foundation
New York Institute of Finance
University of Michigan
University of Virginia Darden School Foundation
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