Summary
In this chapter, we have learned how to identify a suitable ML solution to a business problem and categorize operations to implement suitable MLOps. We set up our tools, resources, and development environment. 10 principles of source code management were discussed, followed by data quality characteristics. Congrats! So far, you have implemented a critical building block of the MLOps workflow – data processing and registering processed data to the workspace. Lastly, we had a glimpse into the essentials of the ML pipeline.
In the next chapter, you will do the most exciting part of MLOps: building the ML pipeline. Let's press on!
