rixwew/pytorch-fm
PyTorch implementation of factorization machines and neural CTR prediction models including DeepFM, DCN, xDeepFM, and Neural Collaborative Filtering.
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This repository provides PyTorch implementations of various factorization machine models and deep learning architectures used for click-through rate prediction and recommendation systems. It includes classical models like FM and FFM alongside deep models such as Wide&Deep, DeepFM, DCN, xDeepFM, and Neural Collaborative Filtering. The package also bundles common benchmark datasets for CTR prediction research.
Frequently asked
- What is rixwew/pytorch-fm?
- PyTorch implementation of factorization machines and neural CTR prediction models including DeepFM, DCN, xDeepFM, and Neural Collaborative Filtering.
- Is pytorch-fm open source?
- Yes — rixwew/pytorch-fm is open source, released under the MIT license.
- What language is pytorch-fm written in?
- rixwew/pytorch-fm is primarily written in Python.
- How popular is pytorch-fm?
- rixwew/pytorch-fm has 1.1k stars on GitHub.
- Where can I find pytorch-fm?
- rixwew/pytorch-fm is on GitHub at https://github.com/rixwew/pytorch-fm.