ML Ops preparing for gcp

## MLOPs Which of the following characteristics of delivering an ML model is considered as a characteristic of maturity level 0? - [ ] Source control automation - [x] Manual, script-driven, and interactive process > Correct Answer - [ ] Feature store integration - [ ] Pipeline continuous integration ## What is the process of monitoring, measuring, retraining, and serving ML models automatically and continuously to adapt to changes in the data before they’re redeployed? - [ ] Continuous delivery - [ ] Continuous integration - [x] Continuous training > Correct Answer - [ ] Continuous deployment ## Which of the following steps is part of continuous integration and delivery (CI/CD) but not continuous training (CT)? - [ ] Measuring the model - [x] Building the model - [ ] Retraining the model - [ ] Monitoring the model ## What is the important aspect of MLOps which differs from DevOps? - [ ] MLOps deploys code and moves to another task. - [ ] MLOps tests and validates only the code and components. - [x] MLOps constantly monitors, retrains, and serves the model. - [ ] MLOps focuses on a single software package or service.