Difference between revisions of "Meteos"
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Meteos allows users to analyze huge amount of data and predict a value by data mining and machine learning algorithms. | 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 create a workspace of Machine Learning via sahara spark plugin and manage some resources and jobs regarding Machine Learning. | ||
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| + | Meteos named from Meteo (Meteorologist) + OS (OpenStack). | ||
== Projects == | == Projects == | ||
Revision as of 02:02, 30 November 2016
Contents
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
