Project Topic: Fraud Detection Application using EvaDB

Introduction

EvaDB enables software developers to build AI apps in a few lines of code. Its powerful SQL API simplifies AI app development for both structured and unstructured data. In this project, we build a basic fraud detection application with EvaDB using built-in Ludwig AI engine.

Run the code

• Google Colab (Recommended)
  • Run on Google Colab
• Local Machine
  • pip install -r requirements.txt
  • python -m run_evadb

Result

We load the Credit Card Fraud Detection into our PostgreSQL database.

This command will download the credit card fraud dataset from Kaggle after data cleaning. The creditcard_fraud dataset contains over 3K records with 11 features and a binary label indicating whether a transaction was fraudulent or not.

The confusion matrix after training with Ludwig autoML

See more details in tutorial