Developed an ensemble of machine learning classifiers to predict the Click Through Rate (CTR) based upon multiple parameters obtained from a click stream history. We used Tensorflow 2.0 to build a Deep Neural Net based Linear Combined classifier to achieve "Memorization" and "Generalization" simultaneously. The results were bench marked against the standard Machine Learning models like logistic regression, Gaussian Naive Bayes, Random forest, KNN, XGBoost and AdaBoost based classifiers.