Python Topic Modeling With a BERT Model

This article discusses topic detection using BERT (Bidirectional Encoder Representations from Transformers), a large language model created and published in 2018. It explains the history of transformer models, including their evolution from Recurrent Neural Networks (RNNs) to more recent NLP architecture models like Gated Recurrent Unit (GRU). The article also introduces BERTopic, an open-source library that uses a BERT model for topic detection with class-based TF-IDF procedure. It demonstrates how to use the BERTopic library in Python for topic modeling and visualizing document clusters.

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