Book Content
chapters • 12h48m total length
1. Challenges in Machine Learning
2. Understanding MLOps
3. Exploring Kubernetes
4. The Anatomy of a Machine Learning Platform
5. Data Engineering
6. Machine Learning Engineering
7. Model Deployment and Automation
8. Building a Complete ML Project Using the Platform
9. Building Your Data Pipeline
10. Building, Deploying and Monitoring Your Model
11. Machine Learning on Kubernetes
