Capturing enough accurate, quality data at scale is a common challenge for individuals and businesses alike. In this article, we outline four ways to source raw data for machine learning, and how to go about annotating it.
For one of the world’s largest technology companies, Lionbridge AI performed sentiment annotation on over 20,000 text records. The data was used to help the client’s text analytics platform reach fluency in 14 languages.
Learn how Lionbridge helped one of the world’s largest social media platforms improve their ad delivery platform by collecting millions of ad reviews from users in a variety of geographic and demographic markets.
In this case study, learn how we helped a leader in natural language text technology scale their software implementation framework into 17 additional languages. We delivered in multiple languages and in the context of 25 projects.