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Difference between revisions of "Meteos"

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* [[Meteos/Usecases| Meteos Use Cases]]
 
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* [[Meteos/Models| Meteos Prediction Models]]
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== Getting Started with Meteos ==
 
== Getting Started with Meteos ==

Revision as of 06:40, 4 December 2016

Meteos (Machine Learning as a Service)

Meteos is Machine Learning as a Service (MLaaS) in Apache Spark.

Meteos allows users to analyze huge amount of data and predict a value by data mining and machine learning algorithms. Meteos create a workspace of Machine Learning via sahara spark plugin and manage some resources and jobs regarding Machine Learning.

Meteos named from Meteo (Meteorologist) + OS (OpenStack).

Projects

Meteos

Source code https://github.com/openstack/meteos
Bug tracker https://bugs.launchpad.net/meteos
Feature tracker https://blueprints.launchpad.net/meteos

Python Meteos Client

Source code https://github.com/openstack/python-meteosclient
Bug tracker https://bugs.launchpad.net/python-meteosclient
Feature tracker https://blueprints.launchpad.net/python-meteosclient

Design & Use Cases

Getting Started with Meteos

Instructions for getting started with Meteos using Devstack are available at: Meteos on Devstack

API

Examples