ranking VS LightFM

Compare ranking vs LightFM and see what are their differences.

ranking

Learning to Rank in TensorFlow (by tensorflow)
Ranking Machine Learning Deep Learning information-retrieval learning-to-rank Recommender Systems
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LightFM

A Python implementation of LightFM, a hybrid recommendation algorithm. (by lyst)
Machine Learning Recommender Python matrix-factorization learning-to-rank recommender-system
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ranking LightFM
1 -
2,714 4,604
0.1% 0.5%
6.3 4.8
about 2 months ago 4 months ago
Python Python
Apache License 2.0 Apache License 2.0
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.

ranking

Posts with mentions or reviews of ranking. We have used some of these posts to build our list of alternatives and similar projects.
  • [D] learning to Rank
    1 project | /r/MachineLearning | 21 Feb 2021
    There are many different models and loss functions used for ranking (Tensorflow Ranking offers a bunch, probably also available for Jax / Pytorch / etc., or easily convertible).

LightFM

Posts with mentions or reviews of LightFM. We have used some of these posts to build our list of alternatives and similar projects.

We haven't tracked posts mentioning LightFM yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing ranking and LightFM you can also consider the following projects:

torchsort - Fast, differentiable sorting and ranking in PyTorch

Surprise - A Python scikit for building and analyzing recommender systems

RecBole - A unified, comprehensive and efficient recommendation library

tensorflow - An Open Source Machine Learning Framework for Everyone

BERT-QE - Code and resources for the paper "BERT-QE: Contextualized Query Expansion for Document Re-ranking".

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

recommenders - Best Practices on Recommendation Systems

MLflow - Open source platform for the machine learning lifecycle

spotlight - Deep recommender models using PyTorch.

xgboost - Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library, for Python, R, Java, Scala, C++ and more. Runs on single machine, Hadoop, Spark, Dask, Flink and DataFlow

rexmex - A general purpose recommender metrics library for fair evaluation.

ranking vs torchsort LightFM vs Surprise ranking vs RecBole LightFM vs tensorflow ranking vs BERT-QE LightFM vs implicit ranking vs recommenders LightFM vs MLflow ranking vs spotlight LightFM vs xgboost ranking vs rexmex LightFM vs spotlight