A unified, comprehensive and efficient recommendation library
Project description
RecBole is developed based on Python and PyTorch for reproducing and developing recommendation algorithms in a unified, comprehensive and efficient framework for research purpose. In the first version, our library includes 53 recommendation algorithms, covering four major categories: General Recommendation, Sequential Recommendation, Context-aware Recommendation and Knowledge-based Recommendation. View RecBole homepage for more information: https://recbole.io
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
File details
Details for the file recbole-1.2.1.tar.gz.
File metadata
- Download URL: recbole-1.2.1.tar.gz
- Upload date:
- Size: 1.9 MB
- Tags: Source
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
f00a94be7bf1c62d7cb5ac52bdd7c6355a499b1eb7e05d652f110fffa9a9d0a8
|
|
| MD5 |
c36fb92284f854ba5423a0d1e02e57db
|
|
| BLAKE2b-256 |
365db71886d4052776c543e0207770004a3fd9292bbcc68b5081f0f06268bacd
|
File details
Details for the file recbole-1.2.1-py3-none-any.whl.
File metadata
- Download URL: recbole-1.2.1-py3-none-any.whl
- Upload date:
- Size: 2.1 MB
- Tags: Python 3
- Uploaded using Trusted Publishing? No
- Uploaded via: twine/6.1.0 CPython/3.11.3
File hashes
| Algorithm | Hash digest | |
|---|---|---|
| SHA256 |
9c9948202011f37eb0a7c6768129313f00d6403ad221ec940d5e2d5d5f33a407
|
|
| MD5 |
56110b0736dce220b371137935ad36de
|
|
| BLAKE2b-256 |
abfe7d606cb7cd2b166a36b100cb9435d21014ceee16c192d972deb0976967a8
|
