c3c46f41dd
Adding the overview document and changed a few documents to make the docs better. Change-Id: Ia1fd7f037f85cc1363678f16232c1d9371fdb292 Partial-Implements: blueprint meteos-docs
1.3 KiB
1.3 KiB
Meteos Overview ==============
What is Meteos?
Meteos is an OpenStack project to provide "Machine Learning as a service".
- Component based architecture: Quickly add new behaviors
- Highly available: Scale to very serious workloads
- Fault-Tolerant: Isolated processes avoid cascading failures
- Recoverable: Failures should be easy to diagnose, debug, and rectify
- Open Standards: Be a reference implementation for a community-driven api
- API Compatibility: Meteos strives to provide API-compatible with popular systems like Amazon EC2
Main use cases
Machine Learning consists of the following phases.
- Learning Phase - Analyze huge amounts of data and create a Prediction Model
- Prediction Phase - Predict a value according to the input value by using Prediction Model
Use case in Learning Phase
- Upload Raw Data - Upload a raw data to Object Storage
- Parse Raw Data - Parse a raw data to enable MLllib (Apache Spark's scalable machine learning library) to handle it. Users are allowed to parse the parsed data again.
- Create Prediction Model - Create a Prediction Model by using MLlib
Use case in Prediction Phase
- Predict - Input any value and retrieve predicted value