Book Content
chapters • 14h total length
1. Getting Started with Automated Machine Learning on AWS
2. Automating Machine Learning Model Development Using SageMaker Autopilot
3. Automating Complicated Model Development with AutoGluon
4. Continuous Integration and Continuous Delivery (CI/CD) for Machine Learning
5. Continuous Deployment of a Production ML Model
6. Automating the Machine Learning Process Using AWS Step Functions
7. Building the ML Workflow Using AWS Step Functions
8. Automating the Machine Learning Process Using Apache Airflow
9. Building the ML Workflow Using Amazon Managed Workflows for Apache Airflow
10. An Introduction to the Machine Learning Software Development Lifecycle (MLSDLC)
11. Continuous Integration, Deployment, and Training for the MLSDLC
