dayyass/latent-semantic-analysis
Pipeline for training LSA models using Scikit-Learn.
This tool helps data scientists and researchers analyze large collections of text documents to uncover hidden themes and relationships between words and documents. You provide a CSV file containing raw text, and it outputs a trained Latent Semantic Analysis (LSA) model, document embeddings, and term embeddings. This is useful for tasks like topic modeling, information retrieval, and text summarization.
No commits in the last 6 months. Available on PyPI.
Use this if you need to quickly train a Latent Semantic Analysis model on your text data without writing extensive code for data preparation or model configuration.
Not ideal if you need highly customized natural language processing pipelines beyond standard TF-IDF and SVD, or if you require real-time text processing capabilities.
Stars
23
Forks
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Language
Python
License
MIT
Category
Last pushed
Oct 12, 2021
Commits (30d)
0
Dependencies
5
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