알고리즘의 영향력은 점차 커지고 있습니다. 머신 러닝은 방대한 데이터 세트를 기반으로 주요 의사결정을 내리기 시작함에 따라, 인간인 우리는 실제 생활에서의 한계점을 충분히 알고 있어야 합니다. 대출 승인, 교통 경로 재설정을 막론하고, 머신 러닝 모델에는 인간의 공유가치가 정확히 반영되어야 합니다. 본 강좌에서는 가장 기본적인 알고리즘부터 완전 자율 알고리즘에 이르기까지 알고리즘의 발전을 살펴보고, 보다 윤리적으로 건전한 알고리즘을 만드는 방법을 논의합니다.
AI 알고리즘 모델과 한계점
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Gain insight into a topic and learn the fundamentals.
14 reviews
Beginner level
No prior experience required
8 hours to complete
Flexible schedule
Learn at your own pace
Skills you'll gain
- Predictive Modeling
- Applied Machine Learning
- AI literacy
- Artificial Intelligence
- Model Training
- Machine Learning
- Data Ethics
- Machine Learning Algorithms
- Responsible AI
- Predictive Analytics
- Model Evaluation
- Ethical Standards And Conduct
- Machine Learning Methods
- Model Optimization
- Artificial Intelligence and Machine Learning (AI/ML)
- Algorithms
Details to know
Shareable certificate
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Assessments
12 assignments
Taught in Korean
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There are 4 modules in this course
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