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Lecture 5 of RT761 Deep Learning covers various aspects of deep learning strategies, including optimizers like Adam, regularization techniques, and the architecture of neural networks. It discusses the importance of feature extraction through convolutional layers, pooling layers, and fully connected layers in convolutional neural networks, along with practical implementation using PyTorch. Additionally, it addresses the requirements for GPU computation and provides a schematic for training artificial neural
- Author
- sweetseoheun1015
- Language
- EN