Exploratory Topic Modelling in Python
Topic modelling is a technique by which documents within a corpus are clustered based on how certain groups of terms are used together within the text. The commonalities between such term groupings tend to form what we would normally call “topics”, providing a way to automatically categorise documents by their structural content, rather than a more metadata-based knowledge system. Using resources held with EHRI's collections, this notebook offers learners an introduction to 'LDA' topic modelling using Python in a step-by-step guide.