이 과정에서는 AI 해석 가능성과 투명성의 개념을 소개합니다. 개발자와 엔지니어에게 AI 투명성이 얼마나 중요한지를 설명합니다. 데이터와 AI 모델 모두에서 해석 가능성과 투명성을 구현하는 데 도움이 되는 실용적인 방법과 도구를 살펴봅니다.
Responsible AI for Developers: Interpretability & Transparency - 한국어
Responsible AI for Developers: Interpretability & Transparency - 한국어
Instructor: Google Cloud Training
Access provided by Coursera Learning Team
Gain insight into a topic and learn the fundamentals.
Intermediate level
Some related experience required
3 hours to complete
3 weeks at 1 hour a week
Flexible schedule
Learn at your own pace
What you'll learn
AI와 관련된 해석 가능성 및 투명성 정의
AI의 해석 가능성 및 투명성이 갖는 중요성 설명
AI에서 해석 가능성 및 투명성을 구현하기 위해 사용하는 도구와 기법 탐구
Details to know
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Assessments
1 assignment
Taught in Korean
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There are 4 modules in this course
이 모듈에서는 과정 구성과 목표를 소개합니다.
What's included
1 video
이 모듈에서는 AI 해석 가능성과 투명성을 중점적으로 다룹니다. 데이터와 AI 모델 모두에서 해석 가능성과 투명성을 구현하는 데 도움이 되는 다양한 기법과 도구를 소개합니다.
What's included
9 videos1 assignment1 app item
이 모듈에서는 가장 중요한 개념, 도구, 기술을 살펴보면서 전체 과정을 요약합니다.
What's included
1 video1 reading
모든 모듈에 대한 학생 PDF 링크
What's included
3 readings
Instructor
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