Abstract: With the rise of deep learning waves, the full force of deep learning methods has hit the Natural Language Process (NLP) and ushered in amazing technological advances in many different application areas of NLP. In this article, we firstly present the development history, main advantages and research situation of deep learning. Secondly, in terms of both feature representation and model theory, we introduces the neural language model and word embedding as the entry point, and present an overview of modeling and implementations of Deep Neural Network (DNN). Then we focus on the newest deep learning models with their wonderful and competitive performances related to different NLP tasks. At last, we discuss and summarize the existing problems of deep learning in NLP with the possible future directions.