Chapter 7 ML project process

Many ML projects get started the wrong way, trying a way to use data rather than using the data to fulfill a need, a need which has a benefit to the organization It is understandable that organizations want to learn from the data they have, but starting without a clear need in mind often leads to wasted efforts because sooner or later it will be discovered that the data available is not sufficient for a useful model.

At the start of a ML project there should be a clear formulated need which should be answered by the model, because ML is only a tool to help to achieve the objectives of the organization

At the beginning there is a need which ML is suitable to fulfill:Smiley face

  • Optimize fertilizer usage
  • Improve user experience
  • Reduce energy cost
  • Increase milk production
The main project phases

Starting with the need the process can be split up in phases as shown below:

The process is not sequential but highly iterative as is described in the next chapters