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๊ด€๋ฆฌ ๋ฉ”๋‰ด

๋ชฉ๋ก๐Ÿง  Deep Learning (8)

Data Science LAB

[Deep Learning] ์ตœ์ ํ™” ๋ฐฉ๋ฒ• ๋น„๊ต (SGD, Momentum, AdaGrad, Adam

1. SGD (ํ™•๋ฅ ์  ๊ฒฝ์‚ฌ ํ•˜๊ฐ•๋ฒ•) ๋งค๊ฐœ ๋ณ€์ˆ˜์˜ ๊ธฐ์šธ๊ธฐ๋ฅผ ๊ตฌํ•ด ๊ธฐ์šธ์–ด์ง„ ๋ฐฉํ–ฅ์œผ๋กœ ๋งค๊ฐœ๋ณ€์ˆ˜ ๊ฐ’์„ ๊ฐฑ์‹ ํ•˜๋Š” ์ผ์„ ๋ช‡ ๋ฒˆ์ด๊ณ  ๋ฐ˜๋ณตํ•˜์—ฌ ์ตœ์ ์˜ ๊ฐ’์— ๋‹ค๊ฐ€๊ฐ€๋Š” ๊ฒƒ ๊ฒฝ์‚ฌ ํ•˜๊ฐ•๋ฒ•๊ณผ๋Š” ๋‹ค๋ฅด๊ฒŒ ๋žœ๋คํ•˜๊ฒŒ ์ถ”์ถœํ•œ ์ผ๋ถ€ ๋ฐ์ดํ„ฐ์— ๋Œ€ํ•ด์„œ๋งŒ ๊ฐ€์ค‘์น˜๋ฅผ ์กฐ์ ˆํ•จ SGD์˜ ๋‹จ์  : ๋น„๋“ฑ๋ฐฉ์„ฑ ํ•จ์ˆ˜(๊ธฐ์šธ๊ธฐ๊ฐ€ ๋‹ฌ๋ผ์ง€๋Š” ํ•จ์ˆ˜)์—์„œ๋Š” ํƒ์ƒ‰ ๊ฒฝ๋กœ๊ฐ€ ๋น„ํšจ์œจ์ ์ž„ - ํŒŒ์ด์ฌ ์ฝ”๋“œ ๊ตฌํ˜„ class SGD: def __init__(self, lr=0.01): self.lr = lr def update(self, params, grads): for key in params.keys(): params[key] -= self.lr * grad[key] 2. Momentum (๋ชจ๋ฉ˜ํ…€) ๋ชจ๋ฉ˜ํ…€์€ '์šด๋™๋Ÿ‰'์„ ๋œปํ•˜๋Š” ๋‹จ์–ด๋กœ ๊ธฐ์šธ๊ธฐ ๋ฐฉํ–ฅ์œผ๋กœ ํž˜์„ ๋ฐ›์•„ ๋ฌผ์ฒด๊ฐ€ ๊ฐ€์†๋œ๋‹ค..

๐Ÿง  Deep Learning 2022. 11. 18. 00:20
Deep Learning๊ณผ Machine Learning ์ฐจ์ด์ 

์ธ๊ณต์ง€๋Šฅ(AI, Artifical Intelligence)์ด๋ž€? ์ธ๊ณต ์ง€๋Šฅ์ด๋ž€ ๊ธฐ๊ณ„๊ฐ€ ์‚ฌ๋žŒ์ฒ˜๋Ÿผ ์Šค์Šค๋กœ ์ƒ๊ฐํ•˜๊ณ  ํŒ๋‹จํ•˜์—ฌ ํ–‰๋™ํ•˜๋„๋ก ํ•˜๋Š” ๊ฒƒ์œผ๋กœ, ์ฃผ๋กœ ์ธ๊ฐ„์˜ ์ง€๋Šฅ์„ ๊ฐ–๊ณ  ์žˆ๋Š” ์ปดํ“จํ„ฐ ์‹œ์Šคํ…œ์„ ์˜๋ฏธํ•œ๋‹ค. ๊ธฐ๊ณ„๊ฐ€ ์ธ๊ฐ„์˜ ์ง€๋Šฅ์„ ๊ฐ€์ง€๊ณ  ์žˆ๋Š” ๋ชจ๋“  ๊ฒƒ์„ ์ธ๊ณต ์ง€๋Šฅ์ด๋ผ๊ณ  ํ•œ๋‹ค. ex) ๋„ค์ด๋ฒ„ ํŒŒํŒŒ๊ณ , ์•ŒํŒŒ๊ณ  ๋“ฑ๋“ฑ ๋จธ์‹ ๋Ÿฌ๋‹(ML, Machine Learning)์ด๋ž€? ์•Œ๊ณ ๋ฆฌ์ฆ˜์„ ์ด์šฉํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ๋ถ„์„, ํ•™์Šต, ํŒ๋‹จ, ์˜ˆ์ธกํ•˜๋Š” ๊ธฐ๋ฒ•์œผ๋กœ ์ œ๊ณต๋œ ๋ฐ์ดํ„ฐ๋ฅผ ํ†ตํ•ด ์Šค์Šค๋กœ ํ•™์Šตํ•˜๋Š” ๊ฒƒ์ด๋‹ค. ex) ์ธ๊ณต ์‹ ๊ฒฝ๋ง, ์˜์‚ฌ๊ฒฐ์ •๋‚˜๋ฌด ๋“ฑ๋“ฑ ๋”ฅ๋Ÿฌ๋‹(DL, Deep Learning) ์ด๋ž€? ๋‡Œ์˜ ๋‰ด๋Ÿฐ๊ณผ ์œ ์‚ฌํ•œ ์ •๋ณด ์ž…์ถœ๋ ฅ ๊ณ„์ธต์„ ํ™œ์šฉํ•˜์—ฌ ๋ฐ์ดํ„ฐ๋ฅผ ํ•™์Šตํ•˜๋Š” ๊ธฐ๋ฒ•์ด๋‹ค. ๋ฐ์ดํ„ฐ ์…‹์„ ๋ถ„๋ฅ˜ํ•˜๊ณ , ๋ฐ์ดํ„ฐ๊ฐ„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ์ฐพ์•„๋‚ด์–ด ์˜ˆ์ธก์„ ๋” ์ •ํ™•ํ•˜๊ฒŒ ..

๐Ÿง  Deep Learning 2022. 2. 13. 01:18