Use Cases Layer of the Machine Learning Platform

Use Cases Layer of the Machine Learning Platform

“Architecture is the reaching out for the truth” — Louis Kahn. The question is: Truth about what? Designing a platform is a continuous search for the truth. Nevertheless, this could be an endless process if the “about what” is not well defined. Use Cases Layer of the Machine Learning Platform

This is the fourth chapter of my journey in building a Machine Learning Platform on AWS. This chapter is based on my work so far presented in the previous parts: the high-level overview of the ML Platform, the infrastructure & software layers, and the framework layer.

In this part, I am going to study the fourth layer of the Machine Learning Platform on AWS: Use cases layer.

1 | So, Truth about what?

When a new use case is selected by stakeholders, comes the ultimate goal of landing this use case on the machine learning platform. Achieving this goal is constrained by solving three riddles:

  • What is the truth behind the use case?
  • What mysteries are hiding behind the data needed for the use case?
  • How to properly land this use case on the machine learning platform?

machine-learning artificial-intelligence data-science aws

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