동선생

This post heavily relies on Andrew Ng's lecture: 심층 신경망 개선하기: 하이퍼파라미터 튜닝, 정규화 및 최적화DeepLearning.AI에서 제공합니다. 딥러닝 스페셜라이제이션의 두 번째 과정에서는 딥러닝 블랙박스를 열어 성능을 향상시키고 좋은 결과를 도출하는 프로세스를 체계적으로 이해합니다. 딥러닝 애www.coursera.orgNormalizationNormalization(정규화) 은 training process의 속도를 높여주는 기법들 중 하나입니다. 주의 해야할 점 중 하나는 test set에도 같은 mean, variance 값을 사용하여 정규화해줘야 올바른 test 결과값이 나온다는 것입니다.Unnormalized cost function과 Norma..

Early stopping is a technique used while training neural networks to prevent the model from overfitting.It basically stops the training process before the model starts to overfit.We monitor the model's performance on a validation set during the training process and stop the training process when the general performance starts to degrade, which indicates that the model is beginning to overfit the..

Deep learning fundamentally requires a large amount of data for effective training.Additionally, to solve the chronic problem of overfitting in deep learning, it needs sufficient high-quality data.However, increasing the amount of data requires significant cost and time, and in some cases, it can be difficult to even collect or process the data.To address this issue, various Data Augmentation te..