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BERTopic project preview

BERTopic

Leveraging transformers and c-TF-IDF to create easily interpretable topic clusters from text.

LicenseMIT
GitHub stars7.5k
Last commit6 days ago
Tags5 topics
Topic Modeling NlpBertopic SuiteCustomer Feedback ClustersMarketingTransformer Topic Clustering
Overview

Why consider BERTopic?

BERTopic is an open-source topic modeling technique written in Python by Maarten Grootendorst. Combining Hugging Face Transformers and class-based TF-IDF (c-TF-IDF), BERTopic clusters large collections of customer feedback, support conversations, and social threads into distinct marketing topics.

Guided learning

Learn BERTopic by building

Practical setup notes, real use cases, and copy-ready examples in one focused guide.

1 min read 2 sections
In this guide2 sections

Overview of BERTopic

BERTopic clusters customer reviews and social complaints into actionable marketing themes.

Quickstart

bash
1pip install bertopic
python
1from bertopic import BERTopic
2topic_model = BERTopic()
3topics, probs = topic_model.fit_transform(customer_reviews)
4print(topic_model.get_topic_info())

BERTopic is licensed under the permissive MIT License.

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BERTopic FAQs

BERTopic is listed as a Marketing tool on TiloBox. Review the overview, features, and official documentation on this page to decide whether it solves your specific workflow.

Start with the project's GitHub repository and official website for supported installation and deployment instructions. Test the setup with representative data or a small project before rolling it out more widely.

BERTopic is listed under the MIT license. Read the complete license text and the project's notices before using, modifying, or distributing the software.

Production readiness depends on your requirements. Review maintenance activity, security practices, documentation, backup and upgrade procedures, and compatibility with your stack; then validate it in a non-production environment.

BERTopic is listed as an alternative to Brandwatch. Compare the core workflow, deployment model, integrations, and licensing against your must-have requirements before switching.