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Topic Modeling from Sentiment using BERTopic, Streamlit, and Snowflake

Home Page: https://sentom.streamlit.app

License: MIT License

Python 100.00%
bertopic snowflake streamlit summit-hackathon

sentom's Introduction

sentom

Streamlit Snowflake Python PyTorch

Sentom (sentiment-topic-modeling) is a simple web application that allows you to do topic modeling on sentiment review using BERTopic. This application is built using Streamlit and Snowflake.

Features ๐Ÿ’ก

Using Sentom, you can:

  • Do topic modeling on sentiment review
  • See the top keywords for each topic

Prerequisites ๐Ÿ“‹

Installation ๐Ÿ› 

  • Clone the repository:
git clone https://github.com/putuwaw/sentom.git
  • Install the requirements:
pip install -r requirements.txt
  • Create secret.toml file in .streamlit folder and fill it with your Snowflake credentials. See Documentation for more information.

  • Run the application:

streamlit run Home.py

License ๐Ÿ“

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgements ๐Ÿ™

BERTopic is a topic modeling technique that leverages hugs transformers and c-TF-IDF to create dense clusters allowing for easily interpretable topics whilst keeping important words in the topic descriptions Thank you to the developers and contributors of this open-source tool. Learn more about BERTopic here.

sentom's People

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