An Implementation of Real and Accurate Cloud Based Fraud Detection System by Using Deep and Machine Learning Techniques

From the last decades deep and machine learning techniques are achieves prominent outcomes in various areas like data analytics, big data processing and cloud classifications. Which makes the real time intelligent models, in this investigation proposes a cloud based fraud detection system by using Fully Convolution Neural Networks (FCNN). Along this deep learning, Gradient Boosting Machine Learning (GBML) technology is incorporated, it permits the real time frauds classification and regression on clouds. Our proposed methodology FCNN and GBML compete with existing models in terms of accuracy, recall, true positive rate and precision