AlonAzrael/keras-aquarium
a small collection of models implemented in keras, including matrix factorization(recommendation system), topic modeling, text classification, etc. Runs on tensorflow.
This project offers pre-built models to help you understand and organize large collections of text or recommend items to users. You can input sparse matrices of user-item ratings, bag-of-words documents, or structured text, and get out recommendations, document topics, or text classifications. It's designed for data scientists and machine learning practitioners who work with text data or build recommendation systems.
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Use this if you need ready-to-use deep learning models for tasks like building a recommendation engine, discovering themes in a large corpus of documents, or classifying text.
Not ideal if you prefer to build deep learning models from scratch or need highly customized architectures beyond the provided implementations.
Stars
14
Forks
2
Language
Python
License
MIT
Last pushed
Jul 12, 2017
Commits (30d)
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