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Apache Mahout

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Claimed by Apache Software Foundation Analyzed 21 minutes ago

Apache Mahout's goal is to build scalable machine learning libraries. With scalable we mean: Scalable to reasonably large data sets. Our core algorithms for clustering, classfication and batch based collaborative filtering are implemented on top of Apache Hadoop using the map/reduce paradigm. ... [More] However we do not restrict contributions to Hadoop based implementations: Contributions that run on a single node or on a non-Hadoop cluster are welcome as well. The core libraries are highly optimized to allow for good performance also for non-distributed algorithms [Less]

144K lines of code

6 current contributors

3 months since last commit

24 users on Open Hub

Low Activity
3.6
   
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Crab - Scikit-Recommender

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  Analyzed about 8 hours ago

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). The engine aims to provide a rich set of components from which you can construct a customized ... [More] recommender system from a set of algorithms. It is designed for scability, flexibility and performance making use of scientific optimized python packages in order to provide simple and efficient solutions that are acessible to everybody and reusable in various contexts: science and engineering. [Less]

4.21K lines of code

0 current contributors

over 6 years since last commit

2 users on Open Hub

Inactive
5.0
 
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MyMediaLite

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  Analyzed about 10 hours ago

MyMediaLite is a recommender system algorithm library. It provides methods for two common tasks in recommender systems/collaborative filtering: rating prediction and item prediction from implicit feedback. MyMediaLite also contains command-line programs that let you use much of the library's functionality without having to program.

174K lines of code

0 current contributors

over 1 year since last commit

1 users on Open Hub

Very Low Activity
5.0
 
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MLPACK C++ machine learning library

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  Analyzed about 17 hours ago

MLPACK is a fast C++ machine learning library with an emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and maximum ... [More] flexibility for expert users. It contains algorithms such as k-means, Gaussian mixture models, hidden Markov models, density estimation trees, kernel PCA, locality-sensitive hashing, sparse coding, linear regression, least-angle regression, etc. [Less]

198K lines of code

55 current contributors

1 day since last commit

1 users on Open Hub

Very High Activity
0.0
 
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Licenses: No declared licenses

oryx

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  Analyzed over 1 year ago

Simple real-time large-scale machine learning infrastructure.

30.8K lines of code

0 current contributors

over 2 years since last commit

0 users on Open Hub

Activity Not Available
5.0
 
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oryxproject

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  Analyzed 23 minutes ago

Oryx 2 (incubating): Lambda architecture on Spark for real-time large scale machine learning

130K lines of code

3 current contributors

about 1 month since last commit

0 users on Open Hub

Low Activity
5.0
 
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