Generate the neural network code

Total Files: {{model.codeGeneration.totalFiles}}

{{model.codeGeneration.percentageComplete | number:1}}%

Scan the data

Scanned {{model.dataScanning.scannedObjects}} / {{model.dataScanning.totalObjects}}

Estimated time remaining: {{(model.dataScanning.timeToLoadEntry * (model.dataScanning.totalObjects - model.dataScanning.scannedObjects) / 1000) | number:2}} seconds

{{model.dataScanning.percentageComplete | number:1}}%

Train the network

Completed {{model.training.completedIterations}} / {{model.training.totalIterations}}

Loss {{model.training.currentLoss | number:3}}

Accuracy {{(model.training.currentAccuracy * 100) | number:1}}

Time per 1000 iterations:

{{model.training.percentageComplete | number:1}}%

Test the network

Completed {{model.testing.completedObjects}} / {{model.testing.totalObjects}}

Accuracy {{(model.testing.accuracy * 100) | number:1}}

{{model.testing.percentageComplete | number:1}}%

Integration API

Endpoint

/api/models/{{model._id}}/process

Use your model

{{testResult | json}}

Model Parameters

{{model.parameters | json}}

Export a Micro-API server

Here, the system can pack up a zip-file containing your trained neural network along with a micro-api server which can execute it.

Start Assembling Bundle

Download Model Parameters

Copying EB Files

Zipping Bundle

Uploading to Mongo

Cleaning Up

Download

/eb-loader-button>