Facebook User Advertisement Click Prediction

Social media has become a large platform to extend one's brand's awareness as it bridges the gap between customer and e-commerce. As online advertisement marketing is in demand, many dealers approach social media application owners for marketing their products so that these companies display the advertisements of the merchandise dealers. Such digital marketing methods have poor audiences targeting. This affects either side as customers aren't getting ads they're curious about and also dealers for paying huge price on a daily basis. The machine learning model analyze the given data and using logistic regression algorithm, predicts probability whether the given user supported attributes is probably going to click on or not. As logistic regression algorithm could be a sigmoid relation between data, such that numbers for training is 67 percent and testing is 33 percent. This will increase the productivity up to 200 percent and effective usage of ad revenue. This model is significantly improved version as compared to last model.