Machine learning models are trained to perform particular tasks. Clustering is one of these tasks. Clustering involves finding patterns in data to organise the data points into meaningful sections and clusters.
In the context of Legal AI and Legal NLP, when dealing with large volumes of documents in an eDiscovery use case, clustering can help to organise similar documents into clusters and surface the most important documents to pay attention to first.