Resources
HGU NMT is open at http://203.252.112.19:8888/
Kor-Eng and Eng-Kor Translation System base on Neural Machine Translation with Proper Noun Dictionary.
Deep Learning Tutorial (PyTorch Camp 2021) by MILAb
Machine learning lectures (1 semester): https://www.youtube.com/playlist?list=PLa_Ee35YDBDdaYMFHBKAdmx8fm8VcTnNY
Deep learning practice code
Deep Learning and PyTorch Lectures at YouTube(2019)
2020 AI Korea '알기쉬운 인공지능' (RNN and NLP) part1 and part2 (in Korean)
Live recording of 2021 Pytorch camp (English lectures)
Talks
"데이타는 어떻게 지능이 되는가" 미래사회와 대안기술 포럼, 2021.01.09
"Introduction to RNN and NLP", @AI Korea 2020 (Zoom), 2020.08.27
PyTorch Summer Camp @HGU (2020.07.15 ~ 2020.07.17)
with DongNyeong Heo, Chungjun Lee
"RNNs and NLP", @StradVision (2020.07.06)
"POSTECH 인공지능연구원 AI CASE STUDY 특강", @POSTECH (2020.07.06)
"Deep Learning Workshop", @G.camp (2020.06.25~06.26)
with D. Heo and C. Lee
"RNN and attention in NLP", @ETRI (2020.2.7)
"Deep Learning Workshop", @G.camp (2020.01.17~01.18)
with H. Eom
"AI and Applications", @HGU 평생교육원 (2019.12.10)
"recurrent neural networks and their applications to NLP", @RIST (2019.10.11)
"memory and representation in recurrent neural networks" @SNU (2019.08.05)
PyTorch Summer Camp @HGU (2019.07.29 ~ 2019.07.31)
with Chanung Jeong, Hayoung Eom, and DongNyeong Heo
Poster presentation @AI Korea 2019 (Yonsei Univ.) (2019.07.26)
Sangchul Hahn, "Self-Knowledge Distillation in Natural Language Processing"
Hayoung Eom, "Alpha-Integration Pooling for Convolutional Neural Networks"
"AI Case Studies", POSCO AI experts training course @POSTECH (2019.06.28)
"mathematical issues in optimization and data manifold of neural networks", @KMS Spring Meeting, (2019.04.20)
"recurrent neural networks and their applications to NLP", @SKKU (2019.03.15)
PyTorch Tutorial @HGU (2019.02.19)
with SangChul Hahn, Chanung Jeong, and Hayoung Eom
POSTECH-HGU Workshop - 'Math in Machine Learning' @POSTECH (2019.01.29)
SangChul Hahn, "Generative Adversarial Networks for Text Generation"
Hayoung Eom, "Pooling Methods for Convolutional Neural Networks"