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