A better way to build ML — why you should be using Active Learning

A better way to build ML — why you should be using Active Learning

A better way to build ML — why you should be using Active Learning

“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. The best AI-driven companies, like Tesla, already use active learning. We think you should too…”

Source: humanloop.com/blog/why-you-should-be-using-active-learning/