Credit Card Fraud Detection Project using Machine Learning
Increases the use of e-commerce, tap and pay systems, online bills payment system etc. Fraudster activities also increases day by day and that will attack online transaction. There are number of ways to protect credit cards transaction including credit card data encryption and tokenization.
From last decade, there has been exponential growth of internet. and it leads to increases the use of e-commerce, tap and pay systems, online bills payment system etc. Fraudster activities also increases day by day and that will attack online transaction. There are number of ways to protect credit cards transaction including credit card data encryption and tokenization. Although these methods are effective in most of the cases but they won’t be fully protect credit card transaction against fraud.
Artificial Intelligence(AI) is parent branch of Machine Learning(ML) that allows computers to learn from previous experience and improve in prediction ability without being programmed. In this project we use Machine Learning(ML) method for credit card fraud detection. Machine Learning model trained and tested on large datasets. This model application focuses on supervised ML Algorithms for credit card fraud detection: Decision Tree, Naive Bayes, Random Forest, Artificial Neural Network.
Credit Card Fraud is a fraudulent transaction that is made by using debit or credit card by an unauthorized user.
Credit Card Fraud Prediction using Machine Learning
Software Requirements :-
- Coding Language : Python
- Implementation: Software Framework.
- Operating system : Windows 10 / 11.
- Graphical User Interface : Tkinter
Hardware Requirement:-
- Input Devices : Keyboard, Mouse.
- System : Pentium i3 Processor.
- Hard Disk : 500 GB.
- RAM : 4 GB.
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