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The problem statement is to predict fraudulent credit card transactions with the help of machine learning models. In this project, we need to analyse customer-level data that has been collected and analysed during a research collaboration of Worldline and the Machine Learning Group.
An analysis for finding out best method for credit card fraud detection. It's an comparison between three different classifiers: ANN, KNN and Decision Trees.
🛡️ Welcome to our Credit Card Fraud Detection project! 💳 Harnessing the formidable prowess machine learning, we're steadfast in our mission to fortify your financial stronghold against deceitful adversaries. Join our crusade for financial resilience,Ensuring every transaction is securely monitored! 🔐💯
This project researched the credit card transaction dataset and tried various machine learning classification models on the dataset to determine the best model that would flag suspicious activity more accurately.
Nothing strengthens better your knowledge in Deep Learning than coding an actual model and application. Take the 5 week challenge with Robert, David and George and join us each Friday for a fun and engaging hands-on coding session using TensorFlow 🎉