Deep Learning vs. Neural Network: What’s the Difference?
March 17, 2025
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Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
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Intermediate Python skills: basic programming, understanding of for loops, if/else statements, data structures
A basic grasp of linear algebra & ML
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딥 러닝 전문화 두 번째 과정에서는 딥 러닝 블랙박스를 열어 성과를 이끌어내고 체계적으로 좋은 결과를 만들어내는 과정을 이해하게 됩니다.
최종적으로, 테스트 세트를 훈련 및 개발하고 딥 러닝 애플리케이션 구축을 위한 바이어스/분산을 분석하는 모범 사례를 배우게 됩니다. 초기화, L2 및 드롭아웃 정규화, 하이퍼파라미터 튜닝, 배치 정규화 및 기울기 검사와 같은 표준 신경망 기술을 사용할 수 있어야 합니다. 미니 배치 기울기 하강법, 모멘텀, RMSprop 및 Adam과 같은 다양한 최적화 알고리즘을 구현 및 적용하고 수렴을 확인하고 TensorFlow에서 신경망을 구현합니다. 딥 러닝 전문화는 딥 러닝의 기능, 과제 및 결과를 이해하고 최첨단 AI 기술 개발에 참여할 수 있도록 준비하는 데 도움이 되는 기본 프로그램입니다. 머신 러닝을 업무에 적용하고, 기술 경력 수준을 높이고, AI 세계에서 결정적인 단계를 완료할 수 있는 지식과 기술을 얻을 수 있는 경로를 제공합니다.
다양한 초기화 방법을 사용하여 살펴보고 실험하고 L2 정규화 및 드롭아웃을 적용하여 모델 과적합을 방지한 다음 기울기 검사를 적용하여 사기 탐지 모델의 오류를 식별합니다.
15 videos4 readings1 assignment3 programming assignments2 app items
고급 최적화, 랜덤 미니배칭 및 학습률 감소 스케줄링을 추가하여 모델 속도를 높여 딥 러닝 도구 상자를 개발하십시오.
11 videos2 readings1 assignment1 programming assignment1 app item
신경망을 빠르고 쉽게 구축한 다음 TensorFlow 데이터세트에서 신경망을 훈련할 수 있는 딥 러닝 프레임워크인 TensorFlow를 살펴보십시오.
11 videos5 readings1 assignment1 programming assignment1 app item
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