Summary
In this chapter, we explored a quick recap of the traditional SDLC and introduced the concept of the ML model development life cycle. We discussed each of the steps that we usually encounter in most AI/ML projects, and then we dived into specific challenges that generally exist in each step. Finally, we covered approaches and best practices that companies have learned over time to help them address some of those common challenges.
In the next chapter, we’ll begin to explore the various different services in Google Cloud that can be used to implement AI/ML workloads.
