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    ๊ณ ๊ธ‰์ปดํ“จํ„ฐ๊ทธ๋ž˜ํ”ฝ์Šค | Software Design

    ๊ณ ๊ธ‰์ปดํ“จํ„ฐ๊ทธ๋ž˜ํ”ฝ์Šค | Software Design

    UML(Unified Modeling Language), ์†Œํ”„ํŠธ์›จ์–ด ๊ฐœ๋…์„ ๋‹ค์ด์–ด๊ทธ๋žจ์œผ๋กœ ๊ทธ๋ฆฌ๊ธฐ ์œ„ํ•ด ์‚ฌ์šฉํ•˜๋Š” ์‹œ๊ฐ์ ์ธ ํ‘œ๊ธฐ๋ฒ•. Class, Sequence, Usecase, Object, State diagram ๋“ฑ์ด ์žˆ๋‹ค. ์—ฌ๊ธฐ์„œ ์•Œ์•„๋ณผ ๊ฒƒ์€ Class Diagram! ๊ฐ€์žฅ ๋งŽ์ด ์‚ฌ์šฉ๋˜๋Š” ๋‹ค์ด์–ด๊ทธ๋žจ์ด๋ฉฐ ์ฝ”๋“œ์˜ ๊ตฌ์กฐ๋ฅผ ํ‘œํ˜„ํ•œ๋‹ค. ํฌ๊ฒŒ ์•„๋ž˜์™€ ๊ฐ™์ด ๋‚˜๋ˆˆ๋‹ค
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    ๊ณ ๊ธ‰์ปดํ“จํ„ฐ๊ทธ๋ž˜ํ”ฝ์Šค | Course Overview

    ๊ณ ๊ธ‰์ปดํ“จํ„ฐ๊ทธ๋ž˜ํ”ฝ์Šค | Course Overview

    ๋ณธ ๊ฐ•์˜๋Š” ํ•œ์–‘๋Œ€ํ•™๊ต ์„๋ฐ•์‚ฌ์ˆ˜์—… ์ค‘ ํ•˜๋‚˜์˜€์œผ๋ฉฐ, KCGS 2022 ์—ฌ๋ฆ„ํ•™๊ต์—์„œ๋„ ์งง๋ง‰ํ•˜๊ฒŒ ๊ฐ•์˜๊ฐ€ ๋œ ์ ์ด ์žˆ์—ˆ๋‹ค. ๋˜ํ•œ ์บ๋ฆญํ„ฐ ์• ๋‹ˆ๋ฉ”์ด์…˜์ด ์ฃผ๋œ ๋‚ด์šฉ์ด๋ผ ํ˜น์‹œ mesh, rendering์„ ์ƒ๊ฐํ•˜๊ณ  ์˜ค์…จ๋‹ค๋ฉด ์ด ๊ฐ•์˜๋Š” ๋งž์ง€ ์•Š์„ ๊ฒƒ์ด๋‹ค
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    ์ธ๊ณต์ง€๋Šฅ๊ฐœ๋ก  | Reinforcement Learning

    ์ธ๊ณต์ง€๋Šฅ๊ฐœ๋ก  | Reinforcement Learning

    ์ธ๊ณต์ง€๋Šฅ ๋ถ„์•ผ์—์„œ ๋จธ์‹ ๋Ÿฌ๋‹(๊ธฐ๊ณ„ํ•™์Šต)์€ ๋‹ค๋Ÿ‰์˜ ๋ฐ์ดํ„ฐ๋ฅผ ํ† ๋Œ€๋กœ ์ปดํ“จํ„ฐ๊ฐ€ ํ•™์Šต์„ ํ•˜๊ฒŒ ๋˜๋Š”๋ฐ, ์ปดํ“จํ„ฐ๊ฐ€ ํ•˜๋Š” ์ž‘์—…์€ ํฌ๊ฒŒ ๋‘ ๊ฐ€์ง€๋กœ ๋‚˜๋‰œ๋‹ค. ํ‘œํ˜„(representation): ๋ฐ์ดํ„ฐ ํ‘œํ˜„, ์ผ๋ฐ˜ํ™”(generalization): ์ฃผ์–ด์ง€์ง€ ์•Š์€ ๋ฐ์ดํ„ฐ ์ฒ˜๋ฆฌ ํ•™์Šต ์ข…๋ฅ˜๋Š” ๋จธ์‹ ๋Ÿฌ๋‹ ์ฒ˜์Œ ๋ฐฐ์šธ ๋•Œ...
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    ์ธ๊ณต์ง€๋Šฅ๊ฐœ๋ก  | Decision Tree

    ์ธ๊ณต์ง€๋Šฅ๊ฐœ๋ก  | Decision Tree

    ํฐ ๋ฒ”์ฃผ ์ฆ‰ heterogenous group์„ ์ž‘์€ homogeneous(๋™์ผํ•œ ๋ชฉํ‘œ ๊ฐ’)๋กœ ๋‚˜๋‰œ๋‹ค. ์ด ๋•Œ ๋‚˜๋‰  ๋•Œ๋Š” best split rule์— ๋”ฐ๋ผ ๋‚˜๋‰˜๊ฒŒ ๋˜๋Š”๋ฐ, ๊ธฐ์ค€์€ ๋‚˜๋ˆ„๋Š”๋ฐ ์žˆ์–ด์„œ ์–ผ๋งˆ๋‚˜ ๋‚˜๋‰œ ๊ฐ’๋“ค์ด ํ•œ ๋ชฉํ‘œ๊ฐ’๋งŒ์œผ๋กœ ๋ถ„๋ฅ˜๋˜์—ˆ๋Š”์ง€(purity)์ด๋‹ค.
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    ์ธ๊ณต์ง€๋Šฅ๊ฐœ๋ก  | Clustering

    ์ธ๊ณต์ง€๋Šฅ๊ฐœ๋ก  | Clustering

    KNN์—์„œ ๋ฐฐ์šด ๋ฐ”์™€ ๊ฐ™์ด ๋น„์Šทํ•œ ๊ฐœ์ฒด๋ฅผ ๋ฌถ์–ด์„œ ๋ถ„๋ฅ˜ํ•˜๋Š” ๋ฐฉ๋ฒ•์ด๋‹ค. ๋Œ€ํ‘œ์ ์ธ Unsupervised learning์˜ ํ˜•ํƒœ๋กœ, labed๋œ ๋ฐ์ดํ„ฐ๊ฐ€ ํ•„์š”์—†๋Š” ํ•™์Šต ๋ฐฉ๋ฒ•์ด๋‹ค. ํด๋Ÿฌ์Šคํ„ฐ๋ง์€ ๋ณดํ†ต ๊ฒ€์ƒ‰ ์—”์ง„์— ํ™œ์šฉ๋˜๋Š”๋ฐ, ์œ ์‚ฌํ•œ ๋‹จ์–ด๊ฐ€ ์ถœํ˜„์ด ๊ธฐ๋Œ€๋˜๋Š” ๊ฒ€์ƒ‰๋œ ๋ฌธ์„œ๋“ค๋ผ๋ฆฌ ๊ฐ™์€ ํด๋Ÿฌ์Šคํ„ฐ๋กœ ๋ฌถ์ด๊ฒŒ ๋œ๋‹ค.