lecture-videos

Lecture video repository with some comments or time stamps

Lectures Wiki (강의들에서 나온 주제별 모음)

Convolutional Neural Networks for Text Classification:
- https://youtu.be/bnmAsFBl4E4#t=1h08m08s (15m 30s)
Fully-Connected Layer Perspective about Convolution:
- https://youtu.be/bnmAsFBl4E4#t=1h31m14s (13m 30s)
Four Different Perspectives of Matrix Multiplications (+ Brief Intro to Low-Rank Factorization):
- https://youtu.be/00rwOWPEiY4#t=2h02m19s (36m 00s)
- Prerequisite: Span, Inner Product
Importance of Zero-centered Activation Function: (need to confirm)
- https://youtu.be/vUimliXeBUY?list=PLep-kTP3NkcNd2S-vXp3u_TXYbUIZclKl&t=3682
- https://youtu.be/Wew7bCVx2gI?list=PLep-kTP3NkcN43rnM4WrOYk7eXeB4s3DM&t=1411
Dead ReLU: (need to confirm)
- https://youtu.be/kZlrHIu1cQ8?list=PLep-kTP3NkcNd2S-vXp3u_TXYbUIZclKl&t=3007 (9m)

빅데이터와 정보검색 강의.
topic modeling, word emvedding, attention models, seq2seq models, question answering, memory networks 등을 다룬다.
강의링크 : https://www.youtube.com/playlist?list=PLep-kTP3NkcNqn2MtzkscRlTDYTiqKjzD

course overview (Lecture 1)
- 앞으로 배울 내용들을 간략하게 정리한다.
- https://www.youtube.com/watch?v=Z-ptwY3fkVQ&list=PLep-kTP3NkcNqn2MtzkscRlTDYTiqKjzD&index=1
topic modeling , word embedding (Lecture 2~4)
- topic modeling, gradient descent, word embedding, negative sampling 등을 다룬다 - 키워드와 다큐먼트의 용어 언급에서 간혹 바꿔 말하는 실수가 있으니 주의
- https://www.youtube.com/watch?v=CCZ6LeanKIc&list=PLep-kTP3NkcNqn2MtzkscRlTDYTiqKjzD&index=2