Chapter 7: Extending the GitLab DevOps Platform with Comet
When you implement a data science project, you should consider that your model could age due to various factors, such as concept drift or data drift. For this reason, your project will probably need constant updates.
In the previous chapter, you learned the fundamental principles related to DevOps, which allow you to move the project from the test phase to the production phase. However, this is not enough to deal with constant updates efficiently. In fact, you may need to develop an automatic or semi-automatic procedure that allows you to pass from the build/test phase to the production phase easily without too many manual interventions.
In this chapter, you will review the basic concepts behind Continuous Integration and Continuous Delivery (CI/CD), two strategies that permit you to easily and automatically update your code and move from building/testing to production efficiently. You will also learn how you can implement...
