Credit Card Fraud Detection Using Machine Learning
Keywords:Applications of Machine Learning, Automated fraud detection, Credit card fraud, Data science, Isolation forest algorithm, Local outlier factor
Machine learning and AI techniques are becoming utilized in conjunction with processing to unravel a superfluity of real world issues. These techniques have proved to be extremely effective, yielding most accuracy with nominal financial investment and additionally saving immense amounts of it slow. To feature to their annual financial gain, nowadays, folks have started look stock investments as a moneymaking possibility. With knowledgeable steerage and intelligent designing, it wills virtually double the annual revenue through stock returns. That said, stock investment still remains a risky proposition for the inexperienced. Usurious wages of the investment consultants as well as a general content regarding the monetary matters among the overall public, deters several from commerce in stocks. The worry of losses additionally acts of stocks as a deterrent to many. These facts propelled to harness the ability of machine learning to predict the movement victimization sentiment analysis on the tweets collected victimization the Twitter API and additionally the closing values of varied stocks, seeked to create a system that forecasts the stock value movement of varied corporations. Such a prediction would greatly facilitate a potential stock capitalist in taking wise to choices which could directly contribute to his profits.
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Copyright (c) 2021 Sanisa Saiju, S. Akshaya Jyothy, Christeena Sebastian, Liss Mathew, Tintu Sabu
This work is licensed under a Creative Commons Attribution 4.0 International License.