Enable Machine Self Learning

elasticfeed.io

elasticfeed is implementation of ICSE class architecture and provides flexible configuration model.

Automatic mode: content recognition, learning and streaming

This mode detects the type of input content and enables (configures) available plugins for storing, distribution and learning sections of JSON `Scenariofile` (see below)

Manual mode: content recognition, learning, distribution and maintenance

This mode allows to configure the `Scenariofile` workflow plugins on every level for each event or hook by simple drag&drop.

JSON

The `Scenariofile` is defined per "FEED PAGE" by simple JSON and can be uploaded by API and also CLI tool. Each section collects and pipes data in order of defined events then plugins.

{
    "enabled": true,
    "storing": {
        "create-entry": {
            "indexer": [
                {
                    "type": "image",
                    "blocking": "true",
                    "setings": {}
                }
            ],
            "crawler": []
        }
    },
    "processing": {
        "feed-maintainer": {
            "scenario": []
        },
        "sensor-update": {
            "sensor": [
                {
                    "type": "location",
                },
                {
                    "type": "weather",
                },
                {
                    "type": "timing",
                }
            ]
        },
    },
    "distribution": {
        "push-entry-to-ui": {
            "pipeline": [
                {
                    "type": "ai-nn-brain",
                    "source": "viewer"
                }
            ]
        }
    },
    "learning": {
        "create-metric": {
            "scenario": [
                {
                    "type": "ai-nn-brian-teacher",
                    "mode": "metric-builder"
                }
            ]
        }
    }
}

Contribution

Please contact me if you are interested in meeting the team and contribution to this project in any programming language (go, php, ruby, js, node.js, objective-c, java…).

See my contact page or please leave your e-mail address here if you want be notified when the open source is released.