songrotek/Deep-Learning-Papers-Reading-Roadmap

If you are a newcomer to the Deep Learning area, the first question you may have is "Which paper should I start reading from?" After reading above papers, you will have a basic understanding of the Deep Learning history, the basic architectures of Deep Learning model(including CNN, RNN, LSTM) and how deep learning can be applied to image and speech recognition issues. The following papers will take you in-depth understanding of the Deep Learning method, Deep Learning in different areas of application and the frontiers. "Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding."