Fraud Detection Model

Developed and implemented a Neural Network model for fraud detection using Python, achieving 95% accuracy on test datasets.

Utilized TensorFlow and Scikit-learn to build, train, and optimize machine learning algorithms for transaction analysis. Created data visualizations with Seaborn to communicate insights, and deployed a user-friendly web application using Streamlit.