Chapter 6. Analyzing an ML pipeline

 

This chapter covers

  • Determining if you have the right ML pipeline before it ossifies
  • Economizing resources in your AI project
  • Performing MinMax analysis on the ML pipeline
  • Interpreting the results of a MinMax analysis

In chapter 5, you learned that as soon as you construct an ML pipeline, it starts ossifying. Consequently, it’s essential for you to ensure you don’t have a wrong and inadequate ML pipeline that’s incapable of fulfilling the business goals of your ML project. The most critical business question about the ML pipeline is, “How well does this pipeline do in business terms?” This chapter shows you how to analyze an ML pipeline and get an answer to that question.

Once you know how well your ML pipeline does in a business sense, you can analyze it to determine if it can meet your business goals. The name of the analysis you’ll want to perform is MinMax.[1] You can do MinMax analysis early in the project, and it consists of two parts, each of which answers a different question:

1 Just in case you’re familiar with the Minimax algorithm from game theory [114], you shouldn’t confuse MinMax analysis with the Minimax algorithm—they’re totally different concepts.

6.1. Why you should care about analyzing your ML pipeline

6.2. Economizing resources: The E part of CLUE

6.3. MinMax analysis: Do you have the right ML pipeline?

6.4. How to interpret MinMax analysis results

6.5. How to perform an analysis of the ML pipeline

6.6. FAQs about MinMax analysis

6.7. Exercises

Summary