Korean translation - Atcold/NYU-DLSP20 GitHub Wiki

Workload distribution

File name Translator Start date Publish date Reviewers
README.md Gio March 22 March 23 atcold
index.md Gio March 22 March 23 atcold
01.md Gio March 22 March 23 atcold
01-1.md Gio March 23 March 25 atcold
01-2.md Gio March 25 March 27 atcold
01-3.md Ryan March 27 April 4 Gio
lecture01.sbv
practicum01.sbv
02.md Chanseok March 24 March 25 Gio
02-1.md Chanseok March 30 April 1 Gio
02-2.md SeungHeon March 27 April 1 Chanseok, Gio
02-3.md Yujin April 4 April 6 SeungHeon
lecture02.sbv
practicum02.sbv
03.md Jinwoo March 27 April 3 Gio
03-1.md Jinwoo March 27 April 3 Gio
03-2.md Wonseon March 27 March 30 Gio
03-3.md Seok Hoan March 27 April 8 Yujin
lecture03.sbv
practicum03.sbv
04.md Choong Hee March 25 March 30 atcold
04-1.md Choong Hee March 27 March 30 atcold
practicum04.sbv
05.md Ryan April 3 April 4 Yujin
05-1.md Jieun March 31 April 6 Yujin
05-2.md Jieun April 1 April 6 Yujin
05-3.md Choong Hee March 30 April 6 Yujin
lecture05.sbv
practicum05.sbv
06.md Yujin April 17 April 20 Gio
06-1.md Yujin April 17 April 26 Gio
06-2.md Junha April 19 May 8 Gio
06-3.md Seok Hoan May 3 May 8 Chanseok
lecture06.sbv
practicum06.sbv
07.md Seok Hoan June 25 August 5 Gio
07-1.md Seok Hoan June 25 August 5 Gio
07-2.md Yujin July 4 July 17 Gio
07-3.md Yujin Sep 5 October 13 Gio
08.md Yujin July 4 August 5 Gio
08-1.md Yujin July 4 July 28 Gio
08-2.md Yujin July 18 July 28 Gio
08-3.md Yujin July 18 August 9 Gio
09.md Choong Hee July 17 August 31 Gio
09-1.md Choong Hee July 18 August 31 Gio
09-2.md Choong Hee July 24 August 31 Gio
09-3.md Choong Hee August 10 August 31 Gio
10.md Chanseok July 17 August 23 Gio
10-1.md SeungHeon August 15 August 25 Gio
10-2.md SeungHeon August 17 September 3 Gio
10-3.md SeungHeon August 26 September 3 Gio
11.md Jinwoo July 18 August 23 Gio
11-1.md Jinwoo August 18 September 19 Gio
11-2.md Choong Hee September 5 November 25 Gio
11-3.md Choong Hee September 5 November 25 Gio
12.md Jieun July 18 August 23 Gio
12-1.md Jieun July 18 August 23 Gio
12-2.md Jieun July 21 August 23 Gio
12-3.md Jieun July 21 August 23 Gio
13.md SeungHeon July 17 August 23 atcold
13-1.md Seok Hoan Aug 17 September 25 Gio
13-2.md Seok Hoan Sep 1 September 25 Gio
13-3.md Seok Hoan Sep 1
14.md Yujin July 18 August 9 Gio
14-1.md Yujin July 18 September 19 Gio
14-2.md Yujin July 18 September 19 Gio
14-3.md Yujin July 18 September 29 Gio

Terminology conventions

Rules

  • ์ค„์ž„๋ง์€ ๊ทธ๋Œ€๋กœ ์“ฐ๊ณ , ์ „์ฒด ์šฉ์–ด๋Š” ๋ฒˆ์—ญ
CNN -> CNN
Convolutional neural nets -> ํ•ฉ์„ฑ๊ณฑ ์‹ ๊ฒฝ๋ง
  • ํ•œ ๋‹จ์–ด์ง€๋งŒ ๋ฒˆ์—ญํ•˜๊ธฐ ์• ๋งคํ•œ ๋‹จ์–ด๋Š” ์Œ์—ญ
Dropout -> ๋“œ๋กญ์•„์›ƒ
encoder -> ์ธ์ฝ”๋”
  • ์ค‘์š” ๋‹จ์–ด๋Š” ์ฒ˜์Œ์—๋งŒ <sup>ํƒœ๊ทธ๋กœ ๊ฐ์‹ธ์„œ ์˜๋ฌธ์œผ๋กœ๋„ ํ‘œ๊ธฐ

์—ญ์ „ํŒŒbackpropagation๋Š” ์ค‘์š”ํ•˜๋‹ค. ์—ญ์ „ํŒŒ๊ฐ€ ๋”ฅ๋Ÿฌ๋‹์˜ ํ•ต์‹ฌ์ด๋‹ค.

  • 3ํšŒ ์ด์ƒ ๋“ฑ์žฅํ•˜๋Š” ์ธ๋ฌผ์˜ ๊ฒฝ์šฐ ์ด๋ฆ„์„ ์•„๋ž˜ Convention์— ๋”ฐ๋ผ ํ•œ๊ธ€๋กœ ํ‘œ๊ธฐ
Frank Rosenblatt์€ ๋งํ–ˆ๋‹ค.
"์™œ ์–€ ๋ฅด์ฟค ๊ต์ˆ˜๋งŒ ํ•œ๊ธ€์ด์•ผ!!"

Terms

Term Targeted Korean
activation ํ™œ์„ฑํ™”
activation function ํ™œ์„ฑํ™” ํ•จ์ˆ˜
adaline ์•„๋‹ฌ๋ผ์ธ
affine transformation ์•„ํ•€ ๋ณ€ํ™˜
(artificial) neural network (์ธ๊ณต) ์‹ ๊ฒฝ๋ง
autoencoder ์˜คํ† ์ธ์ฝ”๋”
autonomous vehicles ์ž์œจ์ฃผํ–‰ (์ฐจ๋Ÿ‰)
backpropagation ์—ญ์ „ํŒŒ
batch normalization ๋ฐฐ์น˜ ์ •๊ทœํ™”
belief-propagaation ์‹ ๋ขฐ ์ „ํŒŒ
bias ํŽธํ–ฅ
chain rule ์—ฐ์‡„ ๋ฒ•์น™
computer vision ์ปดํ“จํ„ฐ ๋น„์ „
contractive autoencoder ์ˆ˜์ถ•ํ˜• ์˜คํ† ์ธ์ฝ”๋”
contrast normalization ๋Œ€๋น„ ํ‰์ค€ํ™”
contrastive divergence ๋Œ€์กฐ ๋ฐœ์‚ฐ
convolution ํ•ฉ์„ฑ
convolutional sparse coding ํ•ฉ์„ฑ๊ณฑ ํฌ์†Œ ์ฝ”๋”ฉ, ํ•ฉ์„ฑ๊ณฑ ์ŠคํŒŒ์Šค ์ฝ”๋”ฉ
cost function ๋น„์šฉ ํ•จ์ˆ˜
cybernetic ์ธ๊ณต๋‘๋‡Œํ•™
deep-learning ๋”ฅ๋Ÿฌ๋‹
dropout ๋“œ๋กญ์•„์›ƒ
dynamic time warping ๋™์  ์‹œ๊ฐ„ ์™œ๊ณก
embedding ์ž„๋ฒ ๋”ฉ
energy-based model ์—๋„ˆ์ง€ ๊ธฐ๋ฐ˜ ๋ชจ๋ธ
ensemble ์•™์ƒ๋ธ”
feature ํŠน์ง•
fire (of neuron) (๋‰ด๋Ÿฐ์˜) ๋ฐœํ™”
fully connected layer ์™„์ „ ์—ฐ๊ฒฐ ๊ณ„์ธต
fully connected network ์™„์ „ ์—ฐ๊ฒฐ ์‹ ๊ฒฝ๋ง
gradient ๊ฒฝ์‚ฌ, ๊ทธ๋ž˜๋””์–ธํŠธ
gradient descent ๊ฒฝ์‚ฌ ํ•˜๊ฐ•๋ฒ•
hidden layer ์€๋‹‰์ธต
hierarchical representation ๊ณ„์ธต์  ํ‘œํ˜„
image classification ์ด๋ฏธ์ง€ ๋ถ„๋ฅ˜
image segmentation ์˜์ƒ ๋ถ„ํ• 
inference ์ถ”๋ก 
Jacobian matrix ์•ผ์ฝ”๋น„์•ˆ ํ–‰๋ ฌ
Jensen's Inequality ์˜Œ์„ผ ๋ถ€๋“ฑ์‹
Jupyter Notebook ์ฃผํ”ผํ„ฐ ๋…ธํŠธ๋ถ
label ๋ ˆ์ด๋ธ”
lane tracking ์ฐจ์„  ์ถ”์ 
latent space ์ž ์žฌ ๊ณต๊ฐ„
layer ๋ ˆ์ด์–ด, ์ธต
layers ๊ณ„์ธต
lecture part A ์ด๋ก  part A
logistic regression ๋กœ์ง€์Šคํ‹ฑ ํšŒ๊ท€
loss function ์†์‹คํ•จ์ˆ˜
L2 norm L2 ์ •๊ทœํ™”
manifold ๋งค๋‹ˆํด๋“œ, ๋‹ค์–‘์ฒด
Nash equilibrium ๋‚ด์‹œ ๊ท ํ˜•
natural language understanding ์ž์—ฐ์–ด ์ดํ•ด
natural language processing ์ž์—ฐ์–ด ์ฒ˜๋ฆฌ
nearest neighbor ์ตœ๊ทผ์ ‘ ์ด์›ƒ
neural ordinary differential equation ๋‰ด๋Ÿด ์ƒ๋ฏธ๋ถ„๋ฐฉ์ •์‹
non-maximum suppression ๋น„์ตœ๋Œ€๊ฐ’ ์–ต์ œ
norm ๋†ˆ
object detection ๊ฐ์ฒด ํƒ์ง€
one-hot ์›-ํ•ซ
parameter ๋งค๊ฐœ ๋ณ€์ˆ˜, ๋ชจ์ˆ˜
pattern recognition ํŒจํ„ด ์ธ์‹
penalty term ๋ฒŒ์น™ ํ•ญ, ํŽ˜๋„ํ‹ฐ ํ•ญ
perceptron ํผ์…‰ํŠธ๋ก 
pooling ํ’€๋ง
practicum ์‹ค์Šต
recurrent neural networks ์ˆœํ™˜ ์‹ ๊ฒฝ๋ง
reflection ๋ฐ˜์‚ฌ
regularization ๊ทœ์ œ
rotation ๋กœํ…Œ์ด์…˜
relative entropy ์ƒ๋Œ€ ์—”ํŠธ๋กœํ”ผ
scaling ์Šค์ผ€์ผ๋ง
self-supervised learning ์ž๊ธฐ์ง€๋„ํ•™์Šต
scalar ์Šค์นผ๋ผ
semantic segmentation ์‹œ๋งจํ‹ฑ ๋ถ„ํ• , ์˜๋ฏธ๋ก ์  ๋ถ„ํ• 
segmentor ๋ถ„ํ• ๊ธฐ
shearing ์ ˆ๋‹จ, ์ „๋‹จ
softmax, soft (arg)max ์†Œํ”„ํŠธ๋งฅ์Šค
sparse coding ํฌ์†Œ ์ฝ”๋”ฉ, ์ŠคํŒŒ์Šค ์ฝ”๋”ฉ
speech recognition ์Œ์„ฑ ์ธ์‹
stochastic gradient descent ํ™•๋ฅ ์  ๊ฒฝ์‚ฌ ํ•˜๊ฐ•๋ฒ•
supervised learning ์ง€๋„ ํ•™์Šต
tensor ํ…์„œ
translation ๋ฒˆ์—ญ
trajectory ์‚ฌ์„ 
unsupervised learning ๋น„์ง€๋„ ํ•™์Šต
visual cortex ์‹œ๊ฐ ํ”ผ์งˆ
weight ๊ฐ€์ค‘์น˜
weighted sum ๊ฐ€์ค‘ํ•ฉ

Names of people

Term Targeted Korean
Alfredo Canziani ์•Œํ”„๋ž˜๋„ ์บ”์ง€์•„๋‹ˆ
Kunihiko Fukishima ์ฟ ๋‹ˆํžˆ์ฝ” ํ›„์ฟ ์‹œ๋งˆ
Yann Lecun ์–€ ๋ฅด์ฟค

Proper Noun

Term Targeted Korean
Anaconda ์•„๋‚˜์ฝ˜๋‹ค
Miniconda ๋ฏธ๋‹ˆ์ฝ˜๋‹ค
PyTorch ํŒŒ์ดํ† ์น˜
Python ํŒŒ์ด์ฌ

Do not translate

Term Explanation
actor critic Actor Ctiric ์•Œ๊ณ ๋ฆฌ์ฆ˜
CNN Convolutional Neural Network ํ•ฉ์„ฑ๊ณฑ ์‹ ๊ฒฝ๋ง
GAN generative adversarial networks ์ƒ์‚ฐ์  ์ ๋Œ€ ์‹ ๊ฒฝ๋ง
GPU Graphic Processing Unit ๊ทธ๋ž˜ํ”ฝ์นด๋“œ
ReLU Rectified linear unit
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