DSBA Lab Seminar with cs224d @Stanford

March 29, 2017 · View on GitHub

Deep Learning for Natural Language Processing

Original course homepage: http://cs224d.stanford.edu/

참여 인원: 지도교수 강필성, 박사과정 김준홍, 김창엽, 통합과정 김형석, 김동화, 박민식, 서승완, 석사과정 김보섭, 김해동, 조수현, 서덕성, 박재선, 이기창, 모경현, 정재윤, 장명준

Schedules

  1. Intro to NLP and Deep Learning & Simple Word Vector representations (Mo, KH)
    • Slide with presentation
  2. Advanced word vector representations (Park, MS)
    • Slide with presentation
  3. Neural Networks and backpropagation (Cho, SH)
    • Slide with presentation
  4. Project Advice, Neural Networks and Back-Prop (Kim, DH)
    • Slide with presentation
  5. Practical tips (Kim, HS)
    • Slide with presentation
  6. Introduction to TensorFlow
    • Skip
  7. Recurrent neural networks (Cho, SH)
    • Slide with presentation
  8. GRUs and LSTMs (Kim, HS)
    • Slide with presentation
  9. Recursive neural networks: for parsing (Lee, GC)
    • Slide with presentation
  10. Recursive neural networks: for different tasks (e.g. sentiment analysis) (Kim, CY)
    • Slide with presentation
  11. Convolutional neural networks: for sentence classification (Lee, GC)
    • Slide with presentation
  12. Applications of DL to NLP (Kim, HD)
    • Slide with presentation