Why you should be using active learning to build ML / Humanloop blog

Data labelling is often the biggest bottleneck in machine learning -- finding, managing and labelling vast quantities of data to build a sufficiently performing model can take weeks or months. Active learning lets you train machine learning models with much less labelled data. We think you should too. In this post we'll explain what active learning is, discuss tools to use it in practice, and show what we're doing at Humanloop to make it easier for you to incorporate active learning in NLP. Imagine that you wanted to build a spam filter for your emails.