Crab VS tensorflow

Compare Crab vs tensorflow and see what are their differences.

Crab

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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Crab tensorflow
- 223
1,173 182,575
0.0% 0.5%
0.0 10.0
over 3 years ago 1 day ago
Python C++
OSI Approved 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.

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.

tensorflow

Posts with mentions or reviews of tensorflow. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2024-04-29.

What are some alternatives?

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

Surprise - A Python scikit for building and analyzing recommender systems

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)

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

Prophet - Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth.

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

Pandas - Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

nptyping - 💡 Type hints for Numpy and Pandas

LightGBM - A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.

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

bodywork - ML pipeline orchestration and model deployments on Kubernetes.