LightFM vs Crab

LightFM

A Python implementation of LightFM, a hybrid recommendation algorithm. (by lyst)

Crab is a ﬂexible, fast recommender engine for Python that integrates classic information ﬁltering recommendation algorithms in the world of scientiﬁc Python packages (numpy, scipy, matplotlib). (by muricoca)

Machine Learning

Source Code

muricoca.github.com

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LightFM		Crab
	Project
-	Mentions	-
4,600	Stars	1,173
0.9%	Growth	-0.4%
4.8	Activity	0.0
4 months ago	Latest Commit	over 3 years ago
Python	Language	Python
Apache License 2.0	License	OSI Approved

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.

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.

Crab

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

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

What are some alternatives?

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

Surprise - A Python scikit for building and analyzing recommender systems

tensorflow - An Open Source Machine Learning Framework for Everyone

python-recsys - A python library for implementing a recommender system

implicit - Fast Python Collaborative Filtering for Implicit Feedback Datasets

nptyping - 💡 Type hints for Numpy and Pandas

MLflow - Open source platform for the machine learning lifecycle

bodywork - ML pipeline orchestration and model deployments on Kubernetes.

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

scikit-learn - scikit-learn: machine learning in Python

spotlight - Deep recommender models using PyTorch.