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ALS Recommender System

About

This is the final project of MA-GY 6973-I/MATH-GA 2080-001 Computational Statistics. We build a parallel alternating least square (ALS) recommender system and compare it with known ALS packages. The test is conducted on both the MovieLens dataset and synthetic data.

Prerequisites

$ pip install -r requirements.txt

Run

$ jupyter-notebook als_recommender.ipynb

Contributor

Contact

Email: xhw202@nyu.edu

Reference

License

MIT License

Copyright (c) 2024 Xinghong Wang

Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.

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