Log transformation, for instance, is applied to diminish skewness, thereby stabilizing variance and normalizing data — a beneficial trait for numerous machine learning algorithms.

Poor data quality is enemy number one to the widespread, profitable use of machine learning. The quality demands of machine learning are steep, and bad data can rear its ugly head twice both in ...

In the second step, educational data mining is conducted using a combination of the text replay data and machine-distilled features of student interactions in order to produce an automated means of ...

But what exactly is dirty data, and why is it such a problem? It’s axiomatic to say that data is the new oil of the digital economy, but this is especially true in fields like machine learning.