QuickML Pipeline Endpoints


The primary outcome of machine learning (ML) pipelines is to create endpoints that can be used to make predictions on new data. These endpoints are created using trained ML models, and they can be used for continuous inference.

Once an ML model is developed and trained, QuickML users can create an endpoint with the latest version of the model. This endpoint can then be used to make predictions on new data. QuickML monitors all endpoints to identify areas where the model can be improved.


Published Model Version

Once a machine learning model has been generated using the QuickML pipeline, a user can choose to publish it as an endpoint with a specific model version. This allows users to deploy and use the model to make accurate predictions.

Models are versioned whenever there is change in pipeline stage configurations for the pipeline execution.

Model Version

Model tester

In order to check the accuracy of the model, a Test the Model component w.r t model versions has been integrated in QuickML endpoints module, in which live requests can be made within the web app using Endpoint URL to test the model’s inference.

Model Tester

Endpoints Authentication

The live endpoints are exposed via REST APIs from QuickML service and they can be accessed with two modes:

  • External OAuth2 authentication
  • Internal authentication

External OAuth2 authentication

The endpoints that are exposed as REST APIs are authenticated with the Zoho accounts OAuth2 mechanism. Users can make the prediction calls externally by generating the tokens from the accounts console.

  • Prediction guidelines: To make the REST API calls, the user should provide the below given details,
  • Request URL: Deployment Url provided in details
  • HTTP Method: POST
  • Headers :
{ 'X-QUICKML-ENDPOINT-KEY' : ************************, 'Authorization': 'Zoho-oauthtoken ', 'CATALYST-ORG': ******** 'Environment': , 'Development/Production' }

To generate an access token, please follow the steps in this document,

  • Scope: QuickML.deployment.READ

Last Updated 2024-02-23 17:29:25 +0530 +0530