Self supervised learning & making use of unlabelled data.
The general supervised learning problem starts with a labelled dataset. It's common though to additionally have a large collection of unlabelled data also. Self supervision techniques are a way to make use of this data to boost performance. In this talk we'll review some contrastive learning techniques that can either be used to provide weak labelled data or to act as a way of pre training for few-shot learning.
Target Audience
machine learning practitioners
