Difference between revisions of "Meteos"

Revision as of 02:44, 5 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 is named from Meteo (Meteorologist) + OS (OpenStack).

Projects

Meteos

Python Meteos Client

Design & Use Cases

• Meteos Architecture

• Meteos Use Cases

• Meteos Dataset and Prediction Model

Getting Started with Meteos

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

API

• Meteos API

Examples

• Predict a Sales by using LinearRegression Model

• Predict Victory or Defeat by using LogisticRegression Model

• Make a Decision by using DecisionTree Model

• Clustering User Preferences by using Kmeans Model

• Recommend Movie by using Recommendation Model