10
MLOps & Monitoring
Advanced Data Science Programming
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Preface
About the Book
1
Advanced Programming
2
Modularization & OOP
3
API & Data Integration
4
Advanced Data Wrangling
5
Feature Engineering
6
Predictive Modeling
7
Interactive Visualization
8
Performance Evaluation
9
Deployment
10
MLOps & Monitoring
Table of contents
10.1
Model performance monitoring (data drift, concept drift)
10.2
Retraining pipelines
10.3
Logging & alerting
10.4
Experiment tracking (MLflow, W&B)
10.5
CI/CD for ML
10.6
Scaling inference
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10
MLOps & Monitoring
10.1
Model performance monitoring (data drift, concept drift)
10.2
Retraining pipelines
10.3
Logging & alerting
10.4
Experiment tracking (MLflow, W&B)
10.5
CI/CD for ML
10.6
Scaling inference
9
Deployment