A.I. Wiki

Active Learning

When you have a large amount of data but lack labels for the entire dataset, you can design a system that queries a user for labels on-the-fly. Active learning is semi-supervised and is useful for when the cost of acquiring labels is high.

You may have seen real world examples of active learning in software such as Facebook, where a user is asked to provide the tag for the photo. Negative tweet recognition on Twitter is another example of collecting a label - positive vs. negative tweet - and storing the data for training a model.

Start a free consultation today

Our AI experts will chat with you and your solutions architect for a 30 min Q&A.

TALK TO A SKYMIND EXPERT