CREDIT CARD FRAUD DETECTION USING MACHINE LEARNING TECHNIQUES

Credit card fraud represents a major issue, resulting in billions of dollars lost annually. Machine learning offers a solution for detecting such fraud by identifying patterns that indicate fraudulent transactions. Credit card fraud encompasses both the physical loss of a credit card and the theft of sensitive credit card information. Various machine learning algorithms can be employed for detection purposes. This project aims to develop a machine learning model specifically designed to identify credit card fraud. The model will be trained on a dataset of historical credit card transactions and evaluated using a separate holdout dataset of unseen transactions.