This tutorial aims to learn the basics of deep learning by hands, and master the basics through combination of paper and exercises. The first folder is named Paper. The papers I have read before the graduate level have not been well organized and retained. I want to update the classic papers on classification, detection, and segmentation from 2012 to the present(Theory and realization). The second folder is named Demo that contains practical and theoretical tutorials for hands-on deep learning. The third folder is the install tutorial series, which contains the installation methods of the most popular deep learning framework Pytorch.