딥러닝 [Course 1] Neural Networks and Deep Learning. W4 - Deep Neural Networks by 하응 2023. 3. 7. [Coursera] Neural Networks and Deep Learning 4주차 강의 (Deep Neural Networks)를 수강하며 작성한 필기 노트입니다. 1. Deep L-layer Neural Network 반응형 2. Forward Propagation in a Deep Network 3. Getting your Matrix Dimensions Right 4. Why Deep Representations? 5. Building Blocks of Deep Neural Networks 6. Forward and Backward Propagation 7. Parameters vs Hyperparameters 반응형 공유하기 게시글 관리 공부하응 '딥러닝' 카테고리의 다른 글 [Course 4] Convolutional Neural Networks. W2 - Deep Convolutional Models: Case Studies (0) 2023.05.04 [Course 4] Convolutional Neural Networks. W1 - Foundations of Convolutional Neural Networks (0) 2023.05.04 [Course 2] Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.W1 - Practical Aspects of Deep Learning (0) 2023.03.08 [Course 1] Neural Networks and Deep Learning. W3 - Shallow Neural Networks (0) 2023.02.07 [Course 1] Neural Networks and Deep Learning. W2 - Logistic Regression as a Neural Network (0) 2023.01.31 관련글 [Course 4] Convolutional Neural Networks. W1 - Foundations of Convolutional Neural Networks [Course 2] Improving Deep Neural Networks: Hyperparameter Tuning, Regularization and Optimization.W1 - Practical Aspects of Deep Learning [Course 1] Neural Networks and Deep Learning. W3 - Shallow Neural Networks [Course 1] Neural Networks and Deep Learning. W2 - Logistic Regression as a Neural Network 댓글
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