Credit Card Fraud Detection


  • Machine Learning


Mentors :

  • Ramkrishna Kamble, Rishabh Gupta & Raghav Gupta

Mentees :

  • 4-6


Credit Card Fraud Detection with Machine Learning is a process of data investigation and the development of a model that will provide the best results in revealing and preventing fraudulent transactions.

Goals for the project:-
1) Understanding the distribution of data that is provided to us.
2) Understand common mistaked made with imbalanced datasets.
3) Determine the Classifiers we are going to use and decide which one has a higher accuracy.
4) Create a Neural Network and compare the accuracy to our best classifier.

Simillar project -https://www.kaggle.com/code/janiobachmann/credit-fraud-dealing-with-imbalanced-datasets/notebook

Prerequisites: N/A. Knowledge of basic python is plus.

Tentative Timeline :

Week Work
Week 1-2 Reading up on Python and basic of Machine Learning
Week 3 Understanding Data, Precocessing, EDA
Week 4 Dealing with imbalanced data
Week 5 Testing Classifiers like logistic regression, Randomforest, SVM, Naive bayes, etc.
Week 6 Final Neural networks testing