Skip to main content

PyTorch implementation of Deep Factorization Machine Models

Project description

Factorization Machine models in PyTorch

This package provides a PyTorch implementation of Deep Factorization Machine ;odels and common datasets in Retail Recommendation.

Available Datasets

Available Models

Model Reference
DeepFM H Guo, et al. DeepFM: A Factorization-Machine based Neural Network for CTR Prediction, 2017.
xDeepFM J Lian, et al. xDeepFM: Combining Explicit and Implicit Feature Interactions for Recommender Systems, 2018.

Environment

conda env create -f environment_conda.yml
source activate environment_conda

Installation

pip install deep-rec

Example

python main.py --device cpu --epoch 2 

API Documentation

https://rixwew.github.io/deep-rec (en construcción)

Licence

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

deep-rec-0.0.4.dev1.tar.gz (6.6 kB view details)

Uploaded Source

Built Distribution

deep_rec-0.0.4.dev1-py3-none-any.whl (8.3 kB view details)

Uploaded Python 3

File details

Details for the file deep-rec-0.0.4.dev1.tar.gz.

File metadata

  • Download URL: deep-rec-0.0.4.dev1.tar.gz
  • Upload date:
  • Size: 6.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for deep-rec-0.0.4.dev1.tar.gz
Algorithm Hash digest
SHA256 66073f77e112096e699dc88b167f9857a92c3e755a04990df4de001f6c20674b
MD5 93057a864f4aeb642cc91a49b87fc466
BLAKE2b-256 6360c16e74a8766a9e344062c909fa9411f8b0fb52c1ae443567288262345851

See more details on using hashes here.

File details

Details for the file deep_rec-0.0.4.dev1-py3-none-any.whl.

File metadata

  • Download URL: deep_rec-0.0.4.dev1-py3-none-any.whl
  • Upload date:
  • Size: 8.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.4.1 importlib_metadata/4.0.1 pkginfo/1.7.0 requests/2.25.1 requests-toolbelt/0.9.1 tqdm/4.60.0 CPython/3.9.4

File hashes

Hashes for deep_rec-0.0.4.dev1-py3-none-any.whl
Algorithm Hash digest
SHA256 aadf7469cd41019e9968294bb1f4f1127dbddb7a386de82842b74e0817bff4df
MD5 e805ca2894d8e2aaef49e56d230e3747
BLAKE2b-256 89b9e067dd35d0cd2a1d99719e3bcaa7becb48e757eb1615b26ef821196d34b3

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page