Real-Time Fraud Detection System
Build an end-to-end real-time fraud detection pipeline using stream processing, ML models, and production monitoring.
Completion5%
What You'll Learn
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Design real-time stream processing architectures
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Implement ML-based anomaly detection models
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Build scalable data pipelines with Apache Kafka
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Deploy models with sub-100ms inference latency
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Set up monitoring, alerting, and model drift detection
Project Modules
Implementation Roadmap
Architecture & Data Ingestion
Design the system architecture and set up Kafka streams for real-time transaction data.
ActiveFeature Engineering Pipeline
Build real-time feature extraction and aggregation layers.
PlannedML Model Training & Serving
Train fraud detection models and deploy with low-latency inference.
PlannedMonitoring & Production Hardening
Add observability, alerting, and model performance tracking.
Planned