Table of Contents
1. Introduction to MLOps
2. Understanding Machine Learning Lifecycle
3. Essential Tools and Technologies in MLOps
4. Data Pipelines and Management in MLOps
5. Model Development and Training
6. Model Optimization Techniques for Performance
7. Efficient Model Deployment and Monitoring Strategies
8. Scalability Challenges and Solutions in MLOps
9. Data, Model Governance, and Compliance in Production Environments
10. Security in Machine Learning Operations
11. Case Studies and Future Trends in MLOps
Index
2. Understanding Machine Learning Lifecycle
3. Essential Tools and Technologies in MLOps
4. Data Pipelines and Management in MLOps
5. Model Development and Training
6. Model Optimization Techniques for Performance
7. Efficient Model Deployment and Monitoring Strategies
8. Scalability Challenges and Solutions in MLOps
9. Data, Model Governance, and Compliance in Production Environments
10. Security in Machine Learning Operations
11. Case Studies and Future Trends in MLOps
Index