Methods of Data Labeling in Machine Learning

Accruing a large amount of data is relatively simple. Data can be scraped, created or copied and then be stored in huge data storages. A key driver in developing an intelligent model, however, is not just a sheer mass of data but also an effective strategy to intelligently label data to add structure and sense to the data. Data labeling can, therefore, be described as a way to organize information depending on its content. This content determines the tag or label to be assigned to a specific piece of information after it has been processed.