Click Through Rate Prediction Leveraging Machine Learning Techniques for Mobile Digital Advertisement
Predicting click-through rates (CTR) is essential for optimizing the effectiveness of mobile advertising campaigns, where accurate prediction of user interactions can significantly enhance revenue generation and ad targeting strategies. This thesis investigates the efficacy of different predictive models, using a dataset composed of impressions and interactions with mobile ads. The models examined