๐Ÿ™‚/Coursera_DL

WEEK5 : Machine Learning Strategy

nueoyhk 2020. 12. 20. 00:39

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  • ML ์ „๋žต
    • training loss
    • validation loss
    • test loss
    • real word loss
  • ML ๋ชจ๋ธ์˜ ๋ชฉํ‘œ๋ฅผ ์„ค์ •ํ•˜๊ธฐ ์œ„ํ•œ ๋ฐฉ๋ฒ•

hyoeun-log.tistory.com/entry/WEEK5-ML-%EB%AA%A8%EB%8D%B8%EC%9D%98-%EB%AA%A9%ED%91%9C-%EC%84%A4%EC%A0%95%ED%95%98%EA%B3%A0-%EB%8B%AC%EC%84%B1%ED%95%98%EA%B8%B0

 

  • avoidable bias / variance์˜ ๋น„๊ต๋ฅผ ํ†ตํ•œ ์ „๋žต ์„ธ์šฐ๊ธฐ

hyoeun-log.tistory.com/entry/WEEK5-avoidable-bias-variance-%EB%B9%84%EA%B5%90%EB%A5%BC-%ED%86%B5%ED%95%9C-%EC%A0%84%EB%9E%B5-%EC%84%B8%EC%9A%B0%EA%B8%B0


Introuduction to ML strategy

 

โญ ํ˜„์žฌ ์ƒํ™ฉ์„ ํŒŒ์•…ํ•˜๊ณ , ๊ทธ์— ๋งž๊ฒŒ ๋Œ€์ฒ˜ํ•˜๋Š” ๊ฒƒ์ด ์ค‘์š”ํ•˜๋‹ค.

 

  • 1. fit training set well on cost function
    • bigger network
    • Adam optimizer ์‚ฌ์šฉ
    • more epoch
  • 2. fit dev set well on cost function
    • regularization
    • more training data
  • 3. fit test set well on cost function
    • bigger dev set
  • 4. perform well in real word
    • change dev set
    • change cost function