Edge AI Deployment Pipeline
Quantize and optimize a complex computer vision model using ONNX and TensorRT for real-time inference on edge devices.
Capstone Investigation
You are in a sandbox environment simulating real infrastructure. Complete ALL steps below in order. You must type commands from memory — no answer keys. Read output carefully — you'll be asked analysis questions based on what you see.
Step 1: Inspect Training Data
Examine the transaction dataset to understand its structure before training.
💡 Use pandas to read and display the first few rows of the transactions parquet file.
Step 2: Analysis: Class Imbalance
🔒 Complete previous steps to unlock
Step 3: Initialize Ray Cluster
🔒 Complete previous steps to unlock
Step 4: Train XGBoost Fraud Detection Model
🔒 Complete previous steps to unlock
Step 5: Analysis: Model Performance
🔒 Complete previous steps to unlock
Step 6: Analysis: False Negative Impact
🔒 Complete previous steps to unlock
Step 7: Deploy Real-Time Stream Processor
🔒 Complete previous steps to unlock
Step 8: Analysis: Production Latency
🔒 Complete previous steps to unlock
Step 9: Set Up Model Monitoring
🔒 Complete previous steps to unlock
Investigation Tips
- • Type 'help' for guidance and current step hints
- • Type 'objectives' to see your full mission
- • Read command output carefully — you'll be tested on it
- • Analysis questions require correct answers to proceed
- • No answer keys — you must know the commands
- • 3 wrong analysis answers reveals the hint
Task Status
Complete all 9 steps in order. Progress: 0/9.