Brain network aims to study the interaction of brain functional regions as a whole system, which plays a very important role for the understanding of brain function and structure, as well as the diagnosis of some brain diseases. As an important tool to analyze brain networks, machine learning has become a new focus of research since, and it can obtain the rules via automatically analyzing data and apply these rules to predict the unknown data. This paper reviews the concepts, methods and applications of brain network analysis, and mainly discusses some related works based on machine learning techniques from the following three aspects, i.e., construction of bran network, feature learning and classification and prediction. Finally, The conclution is drawed, and some new directions for future research is forecasted.