This project contains the model building to classify weather the transaction made by credit card is a legit or Fraudalent Transaction.
As we are moving towards the digital world — cybersecurity is becoming a crucial part of our life. When we talk about security in digital life then the main challenge is to find the abnormal activity.
When we make any transaction while purchasing any product online — a good amount of people prefer credit cards. The credit limit in credit cards sometimes helps us me making purchases even if we don’t have the amount at that time. but, on the other hand, these features are misused by cyber attackers.
To tackle this problem we need a system that can abort the transaction if it finds fishy.
Here, comes the need for a system that can track the pattern of all the transactions and if any pattern is abnormal then the transaction should be aborted.
Today, we have many machine learning algorithms that can help us classify abnormal transactions. The only requirement is the past data and the suitable algorithm that can fit our data in a better form.
#CASE :- We are going to predict whether a credit card transaction is Legit ( Legal ) or Fraud.
#WORK FLOW :-
Credit card data
Data Pre Processing
Data Analysis
Train Test Split
Logistic Regression Model
Model Evaluation
Predictive System