With the computer games evolving continuously and rapidly over the years in terms of their complexity and audiovisual qualities, the game AI (Artificial Intelligence) has been largely neglected. The recent study made by the game design companies show that the quality of the game AI sets the game apart from the other mediocre games. There is an essential need to develop a gaming model that can generate an engaging and realistic experience for the player by creating more challenges which can avoid making the player bored if it’s too easy or frustrating if it is too hard. The personalized user content generation in games would increase the self-motivation in players as they deeply immerse themselves into the virtual gaming world. An adaptive user model is necessary to capture the skills of the player and make use of an automatic game content altering algorithm to meet the needs of the player by capturing the player’s game logs and analyzing them. In this report, I summarize the World of Warcraft Avatar History dataset which is a public asset of the research community, comprising of attributes like level, race, class, location, social guild and understand the gameplay behaviour, interactions, predict why the users are unsubscribing from the game using Deep Learning and enhance the game AI on generating user-tailored contents like bonus levels using the results.