July 2023
Intermediate to advanced
272 pages
9h 16m
English
Content preview from Managing Machine Learning Projects
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10 Post project (sprint Ω)
This chapter covers:
- Looking after an ML system after it’s gone into production
- Dealing with production failures
- Learning from the project and improving practice
The models are integrated in an application, and the application is delivered to production. Now someone must look after it! In addition to dealing with old ML systems and looking after new ones, this chapter addresses what happens to the team after you complete the project. How can you and your team learn from it, and what should be done to make the next project better?
10.1 Sprint Ω backlog
The backlog in table 10.1 lays out the work that the team needs to cover once you’ve delivered a system into production.
Table 10.1 Sprint Ω backlog
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Task # ... |
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