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Difference between revisions of "Meteos"

(Resource (TBD))
(API (TBD))
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* [[Meteos/ExampleRecommend| Recommend Movie by using Recommendation Model]]
 
* [[Meteos/ExampleRecommend| Recommend Movie by using Recommendation Model]]
 
== API (TBD) ==
 
 
=== Experiment Template ===
 
 
* Create Experiment Template
 
** POST /v1/<tenant_id>/templates
 
 
* List Experiment Templates
 
** GET /v1/<tenant_id>/templates
 
 
* Show Experiment Template
 
** GET /v1/<tenant_id>/templates/<template_id>
 
 
* Update Experiment Template
 
** PUT /v1/<tenant_id>/templates
 
 
* Delete Experiment Template
 
** DELETE /v1/<tenant_id>/templates/<template_id>
 
 
=== Experiment ===
 
 
* Create Experiment
 
** POST /v1/<tenant_id>/experiments
 
 
* List Experiments
 
** GET /v1/<tenant_id>/experiments
 
 
* Show Experiment
 
** GET /v1/<tenant_id>/experiments/<experiment_id>
 
 
* Update Experiment
 
** PUT /v1/<tenant_id>/experiments
 
 
* Delete Experiment
 
** DELETE /v1/<tenant_id>/experiments/<experiment_id>
 
 
=== Data Set ===
 
 
* Create Data Set
 
** POST /v1/<tenant_id>/datasets
 
 
* List Data Sets
 
** GET /v1/<tenant_id>/datasets
 
 
* Show Data Sets
 
** GET /v1/<tenant_id>/datasets/<dataset_id>
 
 
* Update Data Set
 
** PUT /v1/<tenant_id>/datasets
 
 
* Delete Data Set
 
** DELETE /v1/<tenant_id>/datasets/<dataset_id>
 
 
==== Data Set Actions====
 
 
* Export Data Set to Object Storage
 
** POST /v1/<tenant_id>/datasets/<dataset_id>/action
 
*** BODY {"export"}
 
 
=== Prediction Model ===
 
 
* Create Prediction Model
 
** POST /v1/<tenant_id>/models
 
 
* List Prediction Models
 
** GET /v1/<tenant_id>/models
 
 
* Show Model
 
** GET /v1/<tenant_id>/models/<moded_id>
 
 
* Update Model
 
** PUT /v1/<tenant_id>/models
 
 
* Delete Model
 
** DELETE /v1/<tenant_id>/models/<model_id>
 
 
==== Prediction Model Actions====
 
 
* Export Prediction Model to Object Storage
 
** POST /v1/<tenant_id>/models/<model_id>/action 
 
*** BODY {"export"}
 
 
=== Learning Job ===
 
 
* Create Learning Job
 
** POST /v1/<tenant_id>/jobs
 
 
* List Learning Jobs
 
** GET /v1/<tenant_id>/jobs
 
 
* Show Learning Job
 
** GET /v1/<tenant_id>/jobs/<job_id>
 
 
* Delete Learning Job
 
** DELETE/v1/<tenant_id>/jobs/<job_id>
 

Revision as of 02:22, 29 November 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.

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

Getting Started with Meteos

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

Design & Use Cases

API

Examples