Does the term "prediction" make you think of divining the future with a classic crystal ball, or perhaps a consultation with the Oracle of Delphi?

Predictive Artificial Intelligence has nothing to do with magic, but rather with concrete reality. In these cases, those of us who create AI applications for businesses (approaches and algorithms designed to deliver desired results) must make important methodological choices regarding data use. The goal is to identify the most functional approach to obtain predictions that are more accurate, time-resistant, and reliable as possible. But how is this done?

In October's Data Diet, we offer a technical perspective and delve into more complex aspects with the latest article by our expert Federico Rucci, published on Medium.