bodywork VS Crab

Compare bodywork vs Crab and see what are their differences.


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)
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bodywork Crab
8 0
316 1,129
3.2% 0.1%
9.7 0.0
3 days ago about 1 year ago
Python Python
GNU Affero General Public License v3.0 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.


Posts with mentions or reviews of bodywork. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2021-05-17.


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 bodywork and Crab you can also consider the following projects:

Surprise - A Python scikit for building and analyzing recommender systems

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

nptyping - 💡 Type hints for Numpy

tensorflow - An Open Source Machine Learning Framework for Everyone

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

Keras - Deep Learning for humans

NuPIC - Numenta Platform for Intelligent Computing is an implementation of Hierarchical Temporal Memory (HTM), a theory of intelligence based strictly on the neuroscience of the neocortex.

gensim - Topic Modelling for Humans

gym - A toolkit for developing and comparing reinforcement learning algorithms.

PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)

MLP Classifier - A handwritten multilayer perceptron classifer using numpy.

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