Quality data labeling, model training and model fine-tuning is critical to achieving AI/ML success. In this webinar, Bernard Lawes will talk through some of the issues that prevent data labeling programs from achieving their goals, and ways to overcome these obstacles.
Learn how Yext, a company that provides a suite of solutions that help organizations manage their online presence and deliver exceptional digital experiences, was able to more than double the number of queries their team was labeling every day while virtually eliminating data waste resulting from poor annotation quality.
Learn how to use the new Data Discovery interface in Label Studio Enterprise to surface your most high-impact data in minutes, versus hours of manual work.
Aaron Schliem, Sr. Solutions Architect at Welocalize, will talk us through the data design lifecycle - from defining the problem you’re trying to solve with data to building your data pipeline - and how to build out your annotation team within that context.