3 years ago

Category: Database, Data

For a long time and especially in our exploration stage in the field of machine learning challenges, we focused on the search for a model that, starting from the data in a particular state, can act to obtain a result in the ranges of accurate we consider acceptable.Well, the field of work to obtain the model is so extensive, complex, and fascinating in itself that it can make us lose sight of the rest of the components involved in a software solution.Therefore our model will be surrounded by another set of problems as complex, extensive, and fascinating as the model itself we have developed, for example: We will then meet the fields of ETL, Data Wrangling and MLOps.As data scientists, it is no longer enough to find a model that will solve the challenge; we have to at least think about all these related areas’ feasibility. Let us suppose for a moment that we manage to secure the data collection pipeline.

We need to deploy in a server this model, and develop an user interface that: Additionally, we will envelope the model in an API to calling as a service by other software.

The model is in another module of the application and is not displayed in this article since it is not our goal to detail it here.

In a nutshell: talk about other aspects close to the model that could be necessary for a complete solution.