As Wikipedia became the largest human knowledge repository , quality measurement of its articles received a lot of attention during the last decade. Most research efforts fo-cused on classification of Wikipedia articles quality by using a different feature set. However, so far, no " golden feature set " was proposed. In this paper, we present a novel approach for classifying Wikipedia articles by analysing their content rather than by considering a feature set. Our approach uses recent techniques in natural language processing and deep learning, and achieved a comparable result with the state-of-the-art.