Difference between revisions of "Meteos"
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* [[Meteos/Howto| How to increase the model accuracy]] | * [[Meteos/Howto| How to increase the model accuracy]] | ||
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+ | == Boston Summit == | ||
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+ | * PPT Slide | ||
+ | https://www.slideshare.net/guchi_hiro/openstack-meteos-machine-learning-as-a-service | ||
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+ | * Demo | ||
+ | https://www.youtube.com/watch?v=1t-OJ6-imHU&t=151s |
Revision as of 21:19, 8 May 2017
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 is 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 |
Meteos UI
Source code | https://github.com/openstack/meteos-ui |
Bug tracker | https://bugs.launchpad.net/meteos-ui |
Feature tracker | https://blueprints.launchpad.net/meteos-ui |
IRC
http://webchat.freenode.net/?channels=openstack-meteos
Design & Use Cases
Getting Started with Meteos
Instructions for getting started with Meteos using Devstack are available at: Meteos on Devstack
API
Examples (CLI)
Examples (GUI)
Tips
Boston Summit
- PPT Slide
https://www.slideshare.net/guchi_hiro/openstack-meteos-machine-learning-as-a-service
- Demo