August 2024
Beginner to intermediate
640 pages
14h 53m
Korean
Content preview from AI를 위한 필수 수학
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394
AI
를 위한 필수 수학
9.11.6
주어진 데이터셋에서 관련 변수에 대한 베이즈 네트워크를 어떻게 구
축할까?
베이즈 네트워크의 그래프 구조는 직접 결정하거나 알고리즘을 통해 데이터로부터 학습할 수
있다. 베이즈 네트워크 알고리즘은 충분히 발전했으며 상용 가능한 알고리즘도 많다. 네트워크
의 구조가 설정되면 네트워크의 특정 변수에 대한 새로운 정보가 올 때 네트워크의 각 변수에
대한 신뢰를 업데이트함으로써 각 노드의 조건부 확률을 쉽게 업데이트할 수 있다. 베이즈 네
트워크의 창시자인 주데아 펄
Judea
Pearl
245
은 이러한 업데이트 과정을 살아 있는 유기 조직과 뉴
런으로 이루어진 생물학적 네트워크에 비유했다. 하나의 뉴런을 자극하면 전체 네트워크가 반
응하여 한 뉴런의 정보가 이웃 뉴런으로 전파되는 원리를 설명했다.
마지막으로 우리에게 익숙한 신경망 역시 베이즈 네트워크라고 생각할 수 있다.
NOTE
데이터에서 패턴을 학습하는 모델
주어진 데이터의 피처들의 결합 확률 분포를 학습하는 베이즈 네트워크와 다른 모델들, 예를 들어 <
Chapter
8
확률적 생성 모델>의 생성 모델에서 접한 모델들과 이 책 앞부분의 결정론적 모델들은 데이터에서 패턴을
감지하고 연관성을 학습할 뿐 처음에 이러한 패턴을 일으키는 원인을 학습하는 것과는 다르다는 것에 주목
해야 ...
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and much more.
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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.
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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.