Key considerations for ML platforms
Designing, building, and operating ML platforms are complex endeavors as there are many different considerations, including the personas, key ML process workflows, and various technical capability requirements for the different personas and workflows. In this section, we will delve into each of these key considerations in depth. Let’s dive in!
The personas of ML platforms and their requirements
In the previous chapter, we talked about building a data science environment for the data scientists and ML engineers who mainly focus on experimentation and model development. In an enterprise setting where an ML platform is needed, there are other personas involved, each with their own specific requirements. At a high level, there are two types of personas associated with the ML platform: ML platform builders and ML platform users.
ML platform builders
ML platform builders have the crucial responsibility of constructing the infrastructure...
