Build a machine learning model to identify fraudulent credit card transactions. Preprocess and normalize the transaction data, handle class imbalance issues, and split the dataset into training and testing sets.

Evaluate the model' s performance using metrics like precision, recall, and F1-score, and consider techniques like oversampling or undersampling for improving results.

Train a classification algorithm, such as logistic regression or random forests, to classify transactions as fraudulent or genuine. Evaluate the model' s performance using metrics like precision, recall, and F1-score, and consider techniques like oversampling or undersampling for improving results.

This repository contains the projects I worked on during my Codsoft internship. Each project focuses on a different machine learning problem, including credit card fraud detection, customer churn prediction, movie genre classification, and SMS spam detection.

Train a classification algorithm, such as logistic regression or random forests, to classify transactions as fraudulent or genuine. Evaluate the model' s performance using metrics like precision, recall, and F1-score, and consider techniques like oversampling or undersampling for improving results.

This code snippet performs fraud detection using machine learning models such as RandomForestClassifier and DecisionTreeClassifier.

No description available

The CODSOFT virtual internship provided hands-on experience in Python and machine learning, covering projects such as Credit Card Fraud Detection, Titanic Survival Prediction, Iris Classification, and Sales Forecasting. 🌐💡

No description available

No description available

This repository contains a credit card fraud detection project that focuses on the application of machine learning techniques to identify fraudulent credit card transactions.

No description available

Machine Learning project for credit card fraud detection using Random Forest – CodSoft Task

First Task of CodSoft

Credit Card Fraud Detection ML Project for CODSOFT Tech Internship

Task5: CREDIT CARD FRAUD DETECTION Data Science project Codsoft Internship

No description available

No description available

Here is Task 5: Credit card fraud detection using machine learning, for my data science internship with Codsoft

My Repository name is CODSOFTJUNE because I have done a internship for Codsoft Company and I made 3 projects such as Titanic Survival Prediction,Iris Flower Classification and Credit Card Fraud Detection System

I completed a virtual internship in the Data Science domain at CodSoft. During the internship, I worked on multiple machine learning projects such as Titanic Survival Prediction, Movie Rating Prediction, Sales Forecasting, Iris Flower Classification, and Credit Card Fraud Detection.

Credit card fraud detection | CodSoft Internship

No description available

No description available

No description available

No description available

CODSOFT Intership - Task 5 Credit Card Fraud Detection

No description available

No description available

This project uses Decision Trees to spot fake credit card transactions. It looks at transaction details to decide if they are real or suspicious, helping to catch fraud quickly.