Automating Data Labeling for Text Classification and Named Entity Recognition
In this eBook, we explore the benefits of adopting automatic data labeling for artificial intelligence and machine learning.
Historically, AI development has focused mostly on model development, but recently we have entered the age of data-centricity. As more teams and organizations start using machine learning in their work, they are focused on iterating using data and need more efficient labeling processes increasingly. Programmatic labeling becomes the only practical option when the dataset is both large enough and it requires a significant amount of expertise to label, as subject-matter experts’ time is rarely a scalable resource. At high rates of change and high volumes, automatic labeling reduces the lag between asking for new labels and receiving them. In this eBook, we explore the benefits of adopting automatic data labeling for text classification and named entity recognition for AI.