In this post we will focus on how to acquire the data needed to train our model. We will discuss everything that should be considered such as the possible problems and inconsistencies present in scraped data sources.

This is the first post of a series to describe all details present in the creation of a model. Each post will focus on a specific step towards the final creation of the Machine Learning Model. This first post will give an overview of the problem we are trying to solve and how to frame it as a Machine Learning problem.