supported by
DATA INJECTION
MODEL DEPLOYMENT
Beta
EDGE-ML FLOW
Machine learning in minutes
Central to edge-ml is our
flow
- with a few simple steps edge-ml lets you record data, label samples, train models and deploy validated embedded machine learning directly on the edge.
1
void
setup() {
2 Recorder *rec = new Recorder("https://app.edge-ml.org", "API_KEY");
3 edgeRecorder = rec->getIncrementalRecorder("DATASET_NAME");
11 }
1 void loop() {
7 value = sensor.read();
8 edgeRecorder->addDataPoint("SENSOR_NAME", value);
11 }
2 Recorder *rec = new Recorder("https://app.edge-ml.org", "API_KEY");
3 edgeRecorder = rec->getIncrementalRecorder("DATASET_NAME");
11 }
1 void loop() {
7 value = sensor.read();
8 edgeRecorder->addDataPoint("SENSOR_NAME", value);
11 }
EDGE-ML CLIENTS
Simple data upload
edge-ml requires minimal initilization and supports upload in real-time as well as in bulk from the edge. Pre-recorded data can be simply drag-and-dropped as CSV files to the edge-ml cloud storage.
Roadmap
