What are some common techniques for improving the performance of a CNN during training?
Improving the performance of a Convolutional Neural Network (CNN) during training is a crucial task in the field of Artificial Intelligence. CNNs are widely used for various computer vision tasks, such as image classification, object detection, and semantic segmentation. Enhancing the performance of a CNN can lead to better accuracy, faster convergence, and improved generalization.
What is the purpose of batch normalization in deep learning models and where is it applied in the given code snippet?
Batch normalization is a technique commonly used in deep learning models to improve the training process and overall performance of the model. It is particularly effective in deep neural networks, such as recurrent neural networks (RNNs), which are commonly used for sequence data analysis, including cryptocurrency prediction tasks. In this code snippet, batch normalization is