๐Ÿค– Computer Science/Artificial Intelligence

1. Basic์ธ๊ณต์ง€๋Šฅ > ๊ธฐ๊ณ„ํ•™์Šต > ๋”ฅ๋Ÿฌ๋‹ > ํŠธ๋žœ์Šคํฌ๋จธMachine LearningSupervised Learning (Data-label)classification: ํŠน์ • ํด๋ž˜์Šค ์˜ˆ์ธกregression: ์ˆ˜์น˜ ์˜ˆ์ธกUnsupervised Learning (unlabled data)clustering - ํŠน์ง• ๊ณ ๋ คํ•ด์„œ ๋ฌถ์ŒReinforcement Learning: ๋‘ ๊ฐ€์ง€ ์„ ํƒExploration: ์ƒˆ๋กœ์šด ํ–‰๋™Exploitation: ๊ธฐ์กด ํ–‰๋™ ์ค‘ ๊ฐ€์žฅ ๋งŒ์กฑ๋„ ๋†’์€ ๊ฒƒ ์„ ํƒ   2. Machine Learning(๊ฐœ๋…)๊ณผ Data(์ข…๋ฅ˜, ๋ชจ์–‘)Datasettraining datavalidation datatest dataTargetPredictionmodel parametermodel hyperpar..
230307 ์ธ์ž… Computer Science/Engineering > Artificial Inteligence > Machine Learning > Deep Learning > Transformer Machine Learning Supervised Learning : labeled datasets ์‚ฌ์šฉ Classification : ๋ถ„๋ฅ˜, ํŠน์ • ํด๋ž˜์Šค๋ฅผ ์˜ˆ์ธก Regression : ์Šค์นผ๋ผ ๊ฐ’(์ˆ˜์น˜)์„ ์˜ˆ์ธก. Unsupervised Learning : unlabeled data ์‚ฌ์šฉ Clustering : ๋น„์Šทํ•œ ํŠน์„ฑ์„ ๊ฐ€์ง„ ๊ทธ๋ฃน์œผ๋กœ ๋‚˜๋ˆ” Reinforcement Learning : reward๋ฅผ ์ตœ๋Œ€ํ™”ํ•˜๋Š” ๋ฐฉํ–ฅ์œผ๋กœ ํ•™์Šต ์ง„ํ–‰ Exploration : Agent๊ฐ€ ์ƒˆ๋กœ์šด ํ–‰๋™ ์ˆ˜ํ–‰, ๋” ๋งŽ์€ ์ •๋ณด ์–ป์Œ..