Predictive analytics allows companies to use multidimensional factors to identify growth opportunities and risks, particularly when used to examine insights found within big data.
Data integrity involves looking at data to ensure data is not only correct, but also applied to accurate context, has been properly collected, stored and more.
Machine learning algorithms fuel machine learning models. They consist of three parts: a decision process, an error function and a model optimization process.
Supervised learning is an approach to machine learning that uses labeled data sets to train algorithms in order to properly classify data and predict outcomes.
