Mastering Machine Learning with R(Second Edition)
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Deployment

If everything is done according to the plan up to this point, it might just come down to flipping a switch and your model goes live. Assuming that this is not the case, here are the tasks for this step:

  1. Deploying the plan.
  2. Monitoring and maintaining the plan.
  3. Producing the final report.
  4. Reviewing the project.

After the deployment and monitoring/maintenance and underway, it is crucial for you and those who will walk in your steps to produce a well-written final report. This report should include a white paper and briefing slide. I have to say that I resisted the drive to put my findings in a white paper as I was an indentured servant to the military's passion for PowerPoint slides. However, slides can and will be used against you, cherry-picked or misrepresented by various parties for their benefit. Trust me, that just doesn't happen with a white paper as it becomes an extension of your findings and beliefs. Use PowerPoint to brief stakeholders, but use that the white paper as the document of record and as a preread, should your organization insist on one. It is my standard procedure to create this white paper in R using knitr and LaTex.

Now for the all-important process review, you may have your own proprietary way of conducting it; but here is what it should cover, whether you conduct it in a formal or informal way:

  • What was the plan?
  • What actually happened?
  • Why did it happen or not happen?
  • What should be sustained in future projects?
  • What should be improved upon in future projects?
  • Create an action plan to ensure sustainment and improvement happen

That concludes the review of the CRISP-DM process, which provides a comprehensive and flexible framework to guarantee the success of your project and make you an agent of change.