A study on Machine Learning Approaches for Player Performance and Match Results Prediction

Cricket is unarguably one of the most popular sports in the world. Predicting the outcome of a cricket match has become a fundamental problem as we are advancing in the field of machine learning. Multiple researchers have tried to predict the outcome of a cricket match or a tournament, or to predict the performance of players during a match, or to predict the players who should be selected as per their current performance, form, morale, etc. using machine learning and artificial intelligence techniques keeping in mind extensive detailing, features, and parameters. We discuss some of these techniques along with a brief comparison among these techniques.

Credit Card Fraud Detection using Machine Learning: A Study

As the world is rapidly moving towards digitization and money transactions are becoming cashless, the use of credit cards has rapidly increased. The fraud activities associated with it have also been increasing which leads to a huge loss to the financial institutions. Therefore, we need to analyze and detect the fraudulent transaction from the non-fraudulent ones. In this paper, we present a comprehensive review of various methods used to detect credit card fraud. These methodologies include Hidden Markov Model, Decision Trees, Logistic Regression, Support Vector Machines (SVM), Genetic algorithm, Neural Networks, Random Forests, Bayesian Belief Network. A comprehensive analysis of various techniques is presented. We conclude the paper with the pros and cons of the same as stated in the respective papers.