mljet VS python-recsys

Compare mljet vs python-recsys and see what are their differences.

mljet

Minimalistic ML-models auto deployment tool (by qnbhd)

python-recsys

A python library for implementing a recommender system (by ocelma)
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mljet python-recsys
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68 1,468
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1.0 0.0
19 days ago over 3 years ago
Python Python
MIT License http://www.gnu.org/copyleft/gpl.html
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.

mljet

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

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

python-recsys

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

We haven't tracked posts mentioning python-recsys yet.
Tracking mentions began in Dec 2020.

What are some alternatives?

When comparing mljet and python-recsys you can also consider the following projects:

Sacred - Sacred is a tool to help you configure, organize, log and reproduce experiments developed at IDSIA.

Surprise - A Python scikit for building and analyzing recommender systems

MindsDB - The platform for customizing AI from enterprise data

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).

Metrics - Machine learning evaluation metrics, implemented in Python, R, Haskell, and MATLAB / Octave

Keras - Deep Learning for humans

H2O - H2O is an Open Source, Distributed, Fast & Scalable Machine Learning Platform: Deep Learning, Gradient Boosting (GBM) & XGBoost, Random Forest, Generalized Linear Modeling (GLM with Elastic Net), K-Means, PCA, Generalized Additive Models (GAM), RuleFit, Support Vector Machine (SVM), Stacked Ensembles, Automatic Machine Learning (AutoML), etc.

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)

bodywork - ML pipeline orchestration and model deployments on Kubernetes.

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

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.

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