Personal Information
Organization / Workplace
Korea Korea, South
Occupation
Actuary, Data Analysis
Industry
Finance / Banking / Insurance
Tags
machine learning
deep learning book
gan
deep learning
generative models
generative adversarial networks
wasserstein gan
wgan
quantum
양자컴퓨터
양자컴퓨팅
activelearning
svm
support vector machine
tensorflow
docker
kkt conditions
variational auto-encoders
denoising auto-encoder
auto-encoders
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Presentations
(11)Likes
(15)Faster R-CNN - PR012
Jinwon Lee
•
7 years ago
PR-207: YOLOv3: An Incremental Improvement
Jinwon Lee
•
4 years ago
YOLO9000 - PR023
Jinwon Lee
•
7 years ago
Deep Learning from scratch 4장 : neural network learning
JinSooKim80
•
4 years ago
Deep Learning from scratch 3장 : neural network
JinSooKim80
•
4 years ago
Deep Learning from scratch 5장 : backpropagation
JinSooKim80
•
4 years ago
Invertible residual networks Review
수철 박
•
4 years ago
[T아카데미] 비개발자를 위한 Git과 Github Page 블로그 만들기
Subin An
•
4 years ago
boosting 기법 이해 (bagging vs boosting)
SANG WON PARK
•
6 years ago
Pycon korea 2018 kaggle tutorial(kaggle break)
Yeonmin Kim
•
5 years ago
Wasserstein GAN 수학 이해하기 I
Sungbin Lim
•
7 years ago
Wasserstein GAN
Bar Vinograd
•
7 years ago
The world of loss function
홍배 김
•
5 years ago
딥러닝 기본 원리의 이해
Hee Won Park
•
6 years ago
텐서플로우 설치도 했고 튜토리얼도 봤고 기초 예제도 짜봤다면 TensorFlow KR Meetup 2016
Taehoon Kim
•
8 years ago
Personal Information
Organization / Workplace
Korea Korea, South
Occupation
Actuary, Data Analysis
Industry
Finance / Banking / Insurance
Tags
machine learning
deep learning book
gan
deep learning
generative models
generative adversarial networks
wasserstein gan
wgan
quantum
양자컴퓨터
양자컴퓨팅
activelearning
svm
support vector machine
tensorflow
docker
kkt conditions
variational auto-encoders
denoising auto-encoder
auto-encoders
See more