libffm vs spotlight

libffm

A Library for Field-aware Factorization Machines (by ycjuan)

spotlight

Deep recommender models using PyTorch. (by maciejkula)

Recommender Systems recommender-system Deep Learning learning-to-rank Python Machine Learning matrix-factorization Pytorch

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libffm		spotlight
	Project
-	Mentions	-
1,594	Stars	2,934
-	Growth	-
0.0	Activity	0.0
about 3 years ago	Latest Commit	over 1 year ago
C++	Language	Python
BSD 3-clause "New" or "Revised" License	License	MIT License

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.

libffm

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

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

spotlight

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

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

What are some alternatives?

When comparing libffm and spotlight you can also consider the following projects:

fastFM - fastFM: A Library for Factorization Machines

LightFM - A Python implementation of LightFM, a hybrid recommendation algorithm.

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

annoy - Approximate Nearest Neighbors in C++/Python optimized for memory usage and loading/saving to disk

TensorRec - A TensorFlow recommendation algorithm and framework in Python.

DeepLearningExamples - State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.

RecBole - A unified, comprehensive and efficient recommendation library

PERSIA - High performance distributed framework for training deep learning recommendation models based on PyTorch.