August 2024
Beginner to intermediate
640 pages
14h 53m
Korean
Content preview from AI를 위한 필수 수학
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193
Chapter 4 -
신경망을 위한 최적화
일반 선형 회귀,
ridge
,
lasso
, 엘라스틱넷은 언제 사용할까?
머신러닝 모델을 구축하는 데 사용할 수 있는 수많은 선택지로 인해 혼란에 빠졌더라도 절대
좌절하지 말자. 어떤 선택이 다른 선택보다 더 나은지, 어떤 상황에서 더 나은지 정확히 알려주
는 수학적 분석이 가능해지기 전까지는 마치 집을 리모델링할 때처럼 많은 재료, 디자인, 구조
(여러 가지 머신러닝 방법 )를 잘 선택하여 최종 제품(머신러닝 모델 )을 만든다고 생각하면 된
다. 이것은 단지 집 꾸미기가 아니라 집 전체를 개조하는 것과 같기 때문에 각 구성 요소들은
모델의 기능과 성능에 영향을 미치지만 모두 우리가 결정해야 한다. 하지만 안심해도 된다. 인
공지능을 다루는 방법은 다양하다!
●
약간의 정규화는 항상 좋다. 가중치의 크기를 제어하고 손실 함수를 최소화하는 데 경쟁 항을 추가하는 것
은 일반적으로 항상 좋다.
●
ridge
회귀는 보통 좋은 선택이다.
L2
노름이 미분 가능하기 때문이다. 이는
L1
노름을 최소화하는 것보다
더 안정적이다.
●
L1
노름을 사용하기로 결정했다면
L1
노름이
0
에서 미분 불가능하더라도
0
에서 부분 미분
subdifferential
또는
부분 기울기
subgradient
를 정의할 수 있다. 예를 들면 이 값을 ...
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I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
I’ve been on the O’Reilly platform for more than eight years. I use a couple of learning platforms, but I'm on O'Reilly more than anybody else. When you're there, you start learning. I'm never disappointed.Amir M.
I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.