Table of Contents
- Challenges in Machine Learning
- Understanding MLOps
- Exploring Kubernetes
- The Anatomy of a Machine Learning Platform
- Data Engineering
- Machine Learning Engineering
- Model Deployment and Automation
- Building a Complete ML Project Using the Platform
- Building Your Data Pipeline
- Building, Deploying and Monitoring Your Model
- Machine Learning on Kubernetes

