Learning Salesforce Einstein by Mohith Shrivastava

Author:Mohith Shrivastava [Shrivastava, Mohith]
Language: eng
Format: azw3
Tags: COM091000 - COMPUTERS / Cloud Computing *, COM005030 - COMPUTERS / Enterprise Applications / Business Intelligence Tools, COM004000 - COMPUTERS / Intelligence (AI) & Semantics
Publisher: Packt Publishing
Published: 2017-06-28T04:00:00+00:00

Train the dataset

To train the dataset, we will need to run a simple GET request to train the API.

The CURL command to train the model is as follows:

curl -X POST -H "Authorization: Bearer <token>" -H "Cache-Control: no-cache" -H "Content-Type: multipart/form-data" -F "name=<name of dataset>" -F "datasetId=<datasetId>" https://api.einstein.ai/v1/vision/train

The response will indicate that the job is queued for training. The following JSON output shows the structure of response JSON object from the training API:

{

"datasetId": 1001310,

"datasetVersionId": 0,

"name": "flowers",

"status": "QUEUED",

"progress": 0,

"createdAt": "2017-03-25T03:27:59.000+0000",

"updatedAt": "2017-03-25T03:27:59.000+0000",

"learningRate": 0.001,

"epochs": 3,

"queuePosition": 1,

"object": "training",

"modelId": "3FIBARDU5LHI5XC7KAO3K2ZQYE",

"trainParams": null,

"trainStats": null,

"modelType": "image"

}

Notice the response returns a string modelId. The modelId is of type string and is used to get the status of the training.

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