Are you looking to improve the quality of your training data? Human-annotated data is the key to successful machine learning – humans are simply better than computers at managing subjectivity, understanding intent, and coping with ambiguity.
For over 20 years, we’ve been helping clients optimize their machine learning models with our global, curated crowd of more than 400,000 people.
Read some of our use cases below to help make your case for human-annotated training data, then share them with your team. See how other companies have gotten more from their machine learning investments with high-quality training data from Appen.
Microsoft’s Bing search engine required large-scale data sets to continuously improve the quality of its search results – and the results needed to be culturally relevant for the global markets they served. Appen delivered results that surpassed expectations. Beyond delivering project and program management, Appen provided the ability to grow rapidly in new markets with high-quality data sets.
Use Case #2: Improving Relevance of Social Media Content
A company needed to improve the personalization of its news feed due to user feedback. To facilitate that, the company’s algorithm required an accurate representation of their user base. With a strong partnership formed between the client and Appen, the 4-week pilot became an ongoing program. Not only did their news feed become much more personalized, but the client can now apply similar processes to address other areas of their site.
With the growth in businesses listed on its site, a leading multilingual search engine needed to verify its local listings. What started with 10 evaluators in one market grew to 440 evaluators in 31 markets. Appen verified and corrected data for more than 750,000 of the client’s business listings. That not only improved the local search listings but also enhanced the user experience.
Interested in how Appen’s human-annotated data can help your company? Click here to connect with one of our experts.