Model Monitoring
Detect data drift, model degradation, and trigger retraining.
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After this skill you can…
- Set up drift detection with Evidently AI
- Define and monitor SLAs for model performance
- Build a retraining trigger pipeline
Prerequisites
Watch (10 videos)
MLOps Essentials: Enabling CloudWatch Logging & Monitoring for AWS ML APIs
→ Monitor ML model performance→ Track request/response data→ Debug Lambda executions
MLOps and Monitoring
→ Monitor ML models in production→ Implement MLOps best practices→ Use Kubernetes for deployment
Model Monitoring for LLMs
→ Track Model Drift→ Detect Model Bias→ Optimize Model Performance
The 7 Lines of Code You Need to Run Faster Real-time Inference // Adrian Boguszewski // Meetup #121
→ Monitor Models→ Track Performance
Model Performance Monitoring and Why You Need it Yesterday // Amit Paka // MLOps Coffee Sessions #42
→ Monitor Model Performance→ Detect Data Drift→ Prevent Model Degradation
Track Your Keras Machine Learning Experiments with Weights & Biases
→ Monitor model performance→ Track model metrics→ Visualize model results
The Not So Talked About Reasons Model Monitoring Fails // Oren Razon // MLOps Meetup #88
→ Monitor Model Performance→ Detect Data Drift→ Improve Model Reliability
Model & Data Drift Deep Dive // Ben Wilson // MLOps Meetup Clips
→ Monitor model performance→ Detect data drift→ Perform model retraining
Introduction: Monitoring and Automations Essentials with LangSmith
→ Monitor AI application performance→ Identify performance issues→ Optimize application performance
Inference in Deep Learning
→ Monitor model performance→ Identify areas for optimization
DeepCamp AI