Nexios provide variety machine learning APIs. Main use cases are classification, regression, forecasting and anomaly detection. So it's more an ML API or MLaaS than a machine learning platform.
You code against their API or API libraries. So it's a black box model approach.
client.datasets.create('coffee-consupmption', data) # or with open('cups_of_coffee.csv') as f: client.datasets.create('coffee-consumption', f)
start_date = datetime.datetime.date(2017, 12, 1) end_date = datetime.datetime.date(2017, 12, 31) client.sessions.create_forecast( 'coffee-consumption', 'cups', start_date, end_date, result_interval=TimeInterval.Day )
import_response = client.imports.import_from_s3( 'test-python-import', 'sample-data', 'some-file.csv', 'us-east-1' )