Catalyst QuickML

Catalyst QuickML is a no-code machine learning pipeline builder service that lets you implement a host of pre-built ML algorithms, operations, and data preprocessing techniques, and connect with datasets to build and publish ML models. After you publish the data pipeline and ML pipeline, you can access the models you create with authenticated endpoints.

Execute QuickML Endpoint

The code snippet given below allows you to pass input data to a published QuickML endpoint, and predict the outcome based on the ML model’s processing. The output returns the prediction of the values of the target column that is defined while creating the ML pipeline.

The quickml component instance is created as shown below, which will not fire a server-side call. You can pass the input data to the model’s endpoint as key-value pairs. The endpoint_key mentioned below is the unique ID of the endpoint published for the ML model configured in your project. The endpoint key and the input data are passed to the predict() method for execution.

// input data
const input_data = {
 	// Enter column name and value as per your dataset
 	"column_name1": "value1", 
 	"column_name2": "value2",
 	"column_name3": "value3"
}
// create a quickml instance
const quickml = app.quickML();
// execute predict method
const result = await quickml.predict("{endpoint_key}",input_data); 
 // Replace {endpoint_key} with the endpoint key copied from the catalyst console
console.log(result);

The syntax of the output received is shown below:

{
'status': 'success', 
 'result': ["results....."]
}