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
Northwestern University
Erasmus University Rotterdam
University of California, Davis
Erasmus University Rotterdam
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