This Data Science-like project is aimed on analyzing a bunch of techniques for False Negatives (Frauds classified as Non-Frauds) in a extreme imbalanced dataset - Financial Fraud and improving the predictors performance.
An implementation of a distributed machine learning algorithm using Spark able to identify fraud in credit card transactions
Production-ready fraud detection system using TensorFlow autoencoders with optimized CPU-GPU parallel processing. Features efficient ETL pipelines, Docker containerization, and TensorFlow Serving for deployment. Processes financial transactions in real-time with scalable inference capabilities.
An ML application which catches credit card frauds
Finding the doctors who are taking unethical use of their insurance funds
Classificando dados anônimos de transações por cartão de crédito como fraudulentas ou genuínas
This Data Science-like project is aimed on analyzing a bunch of techniques for False Negatives (Frauds classified as Non-Frauds) in a extreme imbalanced dataset - Financial Fraud and improving the predictors performance.
Classifying of fraudulent credit card transactions so that customers are not charged for items they did not purchase.
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