Credit card fraud detection using machine learning

A web application for analyzing bank transactions and detecting fraud.

Main functions:

• data set preparation,
• use of machine learning algorithms,
• report with graphs, tables and transaction analysis

Additionally:

• comparison of the operation and accuracy of the three algorithms.

Preview

Technologies used

1. Python v3+
2. Machine learning libraries
3. Streamlit

How to run

1. Import all libraries
2. Import streamlit using "import streamlit as st"
3. "streamlit run main.py" in terminal

Dataset

The project uses a free set of data from free access, which includes a collection of credit card transactions, both legitimate and fraudulent. The data set serves as the basis for training and evaluating the fraud detection model. We took the data set from the website kaggle.com. This site is an online resource and community for data science, machine learning and data research specialists.