12 Holding on to your gains by watching for drift

This chapter covers

  • Identifying and monitoring for drift in production solutions
  • Defining responses to detected drift

In the preceding chapter, we established the foundations for measuring the effectiveness of an ML solution. This solid base enables a DS team to communicate to the business about the performance of a project in terms that are relevant to the business. To continue making (hopefully) positive reports about the effectiveness of a solution, a bit more work needs to be done.

If proper attribution monitoring and reporting to the business are the bedrock and foundation of a project, entropy is the buffeting storm seeking to continuously tear down the project. We call this chaotic shift ...

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