Fraud Detection model based on anonymized credit card transactions
It is important that credit card companies are able to recognize fraudulent credit card transactions so that customers are not charged for items that they did not purchase.
The datasets contains transactions made by credit cards in September 2013 by european cardholders. This dataset presents transactions that occurred in two days, where we have 492 frauds out of 284,807 transactions. The dataset is highly unbalanced, the positive class (frauds) account for 0.172% of all transactions.
- get the code from the repository
git clone https://github.com/sagnikghoshcr7/Credit-Card-Fraud-Detection.git
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download the dataset that will be used to train a transaction classifier. Unzip it and put the content (creditcard.csv) under main folder (Credit-Card-Fraud-Detection)
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install required python packages if previously not installed
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Finally run on Jupyter Notebook and enjoy 😉
