Topic: "financial-fraud"
sergio11/online_payment_fraud
🚨 Fraud Detection with Deep Neural Networks (PoC) 🤖 A hands-on personal project to predict fraudulent financial transactions using deep learning. Covers the full pipeline: from exploratory data analysis (EDA) and preprocessing to model training and evaluation. An experimental approach to tackling real-world financial fraud. 📊🔍
Language: Jupyter Notebook - Size: 1.78 MB - Last synced at: 17 days ago - Pushed at: 2 months ago - Stars: 6 - Forks: 2
Alekla0126/Card_Fraud_Detection
Credit Fraud Detection for the course project for the master's degree in Software and Systems Engineering.
Language: Jupyter Notebook - Size: 127 MB - Last synced at: almost 2 years ago - Pushed at: almost 2 years ago - Stars: 3 - Forks: 1
StrangeCoder1729/FinancialFraudDetectionModels
Developed and evaluated machine learning and deep learning models for detecting financial fraud.
Language: Jupyter Notebook - Size: 2.58 MB - Last synced at: 9 months ago - Pushed at: over 1 year ago - Stars: 2 - Forks: 1
kamlesh-IY9/Credit-Card-Transactions-Fraud-Detection-by-Afame-Technologies
🛡️ Welcome to our Credit Card Fraud Detection project! 💳 Harnessing the formidable prowess machine learning, we're steadfast in our mission to fortify your financial stronghold against deceitful adversaries. Join our crusade for financial resilience,Ensuring every transaction is securely monitored! 🔐💯
Language: Jupyter Notebook - Size: 1000 KB - Last synced at: 8 months ago - Pushed at: 8 months ago - Stars: 1 - Forks: 1
dylanperdigao/LIF-Neuron-Alternatives
Source code of the paper entitled "Spiking Alternatives for the Leaky Integrate-and-Fire Neuron: Applications in Cybersecurity and Financial Threats", and presented at IbPRIA 2025, the 12th Iberian Conference on Pattern Recognition and Image Analysis.
Language: Jupyter Notebook - Size: 24.6 MB - Last synced at: 6 days ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0
KarthikSundaram4419/AutoAnomalyDetect
A sophisticated platform for anomaly detection in transaction data using autoencoders. Integrates SQL database connectivity, hyperparameter optimization, entropy analysis, and comprehensive visualizations. Tailored for financial fraud detection and industrial data analytics. (280 characters)
Language: Python - Size: 4.88 KB - Last synced at: 4 months ago - Pushed at: 4 months ago - Stars: 0 - Forks: 0
neavepaul/Financial-Fraud-Detection
Application built for example financial company that predicts if a transaction is fraudulent. Model trained on sample data from kaggle
Language: Jupyter Notebook - Size: 18.5 MB - Last synced at: over 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
