Topic modeling¶

Topic modeling is an unsupervised machine learning technique that discovers abstract “topics” recurring across a collection of documents. Classical algorithms like LDA (Latent Dirichlet Allocation) and modern transformer-based approaches like BERTopic identify thematic clusters without requiring labeled training data.