dataset-sample-split

Essentially, Machine Learning is about learning from data. Therefore, having "good" data leads to better models and more importantly, the quality of information being applied to it plays a crucial role in improving the prediction accuracy.

In this article, we will expose best practices for randomization when separating the data into training and validation sets, as well as the use of a developed routine to execute such tasks.