• Prof. Bharati Pandhare
• Siddharth Patil
• Tejal Dadaji Bhamare
• Sanket borade

Credit card transactions have become common location these days and so are the frauds related to it. One of the most commonplaces to carry out fraud is to acquire the card facts illegally and use it to make on line purchases. For credit card businesses and merchants, it's far in-viable to detect these fraudulent transactions among heaps of regular transactions. If enough statistics is gathered and made available, device mastering algorithms may be implemented to remedy this problem. In this work, popular supervised and unsupervised device getting to know algorithms were implemented to discover credit card frauds in a enormously imbalanced dataset. It was found that unsupervised machine learning algorithms can cope with the skewness and give nice classification results

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"CREDIT CARD FRAUD DETECTION USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 3, page no.1357-1361, March-2021, Available :http://www.jetir.org/papers/JETIR2103184.pdf

"CREDIT CARD FRAUD DETECTION USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 3, page no. pp1357-1361, March-2021, Available at : http://www.jetir.org/papers/JETIR2103184.pdf