1. Introduction

Deep leaning has been developing very fast in recent years due to big data, high-performance computing and the breakthrough of neural network training techniques. It has been particularly successful in computer vision, machine translation, speech recognition and natural language processing. Modern astronomy concerns a big data challenge owning to high-resolution, high-precision and high-cadence telescopes. The big data presents a great challenge to data processing, statistical analysis and scientific discovery. Therefore, it is highly demanded to develop artificial intelligent algorithms to process big data aromatically, further discover complex relationship and mine knowledge hidden in massive data. As the best representative of artificial intelligence, a bunch of classical models have been developed for processing single image, video, speech and natural language. Among of them, convolutional neural network has been verified most efficient for processing image. To process time series input, like video, recurrent neural network, e.g., long short-term memory (LSTM), was developed, which was widely known for forecasting the future, e.g., event occurrence, physical parameter prediction. An overview of artificial intelligence, deep learning and astronomical big data is presented in this chapter, as the background of this book.