MLlib is a Spark implementation of some common machine learning algorithms and utilities, including classification, regression, clustering, collaborative filtering, dimensionality reduction and lot more.

MLIB - Apache Spark's scalable machine learning library

OpenMOLE (Open MOdeL Experiment) makes it simple to execute your programs on distributed computing environments. If you want to execute the same program for many different inputs (parameters or datasets).  The typical usages of OpenMOLE are high performance model calibration, model exploration, machine learning, optimization, data processing. It is a scientific workflow engine that works with your own programs and on your own execution environments.

OpenMOLE - Execute programs on distributed computing environments

PredictionIO is an open source machine learning server for software developers to create predictive features, such as personalization, recommendation and content discovery. It helps to predict user behaviors. 

PredictionIO - Machine Learning Server

MMLSpark provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets.MMLSpark requires Scala 2.11, Spark 2.1+, and either Python 2.7 or Python 3.5+. See the API documentation for Scala and for PySpark.
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Its features include : <BR>
<ul>
<li>Easily ingest images from HDFS into Spark  </li>
<li>Pre-process image data using transforms from OpenCV </li>
<li>Featurize images using pre-trained deep neural nets using CNTK </li>
<li> Use pre-trained bidirectional LSTMs from Keras for medical entity extraction</li>
<li>Train DNN-based image classification models on N-Series GPU VMs on Azure</li>
<li>Train classification and regression models easily via implicit featurization of data </li>
<li>Compute a rich set of evaluation metrics including per-instance metrics</li>
</ul>

MMLSpark provides a number of deep learning and data science tools for Apache Spark, including seamless integration of Spark Machine Learning pipelines with Microsoft Cognitive Toolkit (CNTK) and OpenCV, enabling you to quickly create powerful, highly-scalable predictive and analytical models for large image and text datasets.MMLSpark requires Scala 2.11, Spark 2.1+, and either Python 2.7 or Python 3.5+. See the API documentation for Scala and for PySpark.

MMLSpark - Microsoft Machine Learning for Apache Spark

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MLIB - Apache Spark's scalable machine learning library

OpenMOLE - Execute programs on distributed computing environments

PredictionIO - Machine Learning Server

MMLSpark - Microsoft Machine Learning for Apache Spark

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MLIB - Apache Spark's scalable machine learning library

OpenMOLE - Execute programs on distributed computing environments

PredictionIO - Machine Learning Server

MMLSpark - Microsoft Machine Learning for Apache Spark

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