Contents

recommenders 1.2.0

0

Recommenders - Python utilities for building recommendation systems

Recommenders - Python utilities for building recommendation systems

Stars: 18482, Watchers: 18482, Forks: 3041, Open Issues: 160

The recommenders-team/recommenders repo was created 5 years ago and the last code push was Yesterday.
The project is extremely popular with a mindblowing 18482 github stars!

How to Install recommenders

You can install recommenders using pip

pip install recommenders

or add it to a project with poetry

poetry add recommenders

Package Details

Author
Recommenders contributors
License
None
Homepage
https://github.com/recommenders-team/recommenders
PyPi:
https://pypi.org/project/recommenders/
Documentation:
https://recommenders-team.github.io/recommenders/intro.html
GitHub Repo:
https://github.com/microsoft/recommenders

Classifiers

  • Scientific/Engineering/Artificial Intelligence
  • Software Development/Libraries/Python Modules
No  recommenders  pypi packages just yet.

Errors

A list of common recommenders errors.

Code Examples

Here are some recommenders code examples and snippets.

GitHub Issues

The recommenders package has 160 open issues on GitHub

  • [ASK] Question on ndcg_at_k calculation
  • [BUG] ndcg_at_k() arg error
  • [ASK] Remove deprecated Python settings from devcontainers.json
  • [FEATURE] Improve setup for developers with GPU and Spark details
  • [FEATURE] Add functional test with SAR deep dive notebook
  • [BUG] SAR needs to be modified due to a breaking change in spicy
  • [BUG] error in test deeprec with gzip file
  • [BUG] Review TFIDF notebook and CORD dataset
  • [BUG] Review GeoIMC movielens
  • Add support for Python 3.10 and 3.11 and drop for 3.7
  • How to improve the performance of NCF models

See more issues on GitHub

Related Packages & Articles

auto_ml 2.9.10

Automated machine learning for production and analytics

fiftyone 0.24.1

FiftyOne: the open-source tool for building high-quality datasets and computer vision models

rexmex 0.1.3

A General Purpose Recommender Metrics Library for Fair Evaluation.

pytorch-lightning 2.3.3

PyTorch Lightning is the lightweight PyTorch wrapper for ML researchers. Scale your models. Write less boilerplate.

spacy 3.7.5

Industrial-strength Natural Language Processing (NLP) in Python