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Learning Salesforce Einstein

You're reading from   Learning Salesforce Einstein Add artificial intelligence capabilities to your business solutions with Heroku, PredictiveIO, and Force

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Product type Paperback
Published in Jun 2017
Publisher Packt
ISBN-13 9781787126893
Length 334 pages
Edition 1st Edition
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Author (1):
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Mohit Shrivatsava Mohit Shrivatsava
Author Profile Icon Mohit Shrivatsava
Mohit Shrivatsava
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Table of Contents (10) Chapters Close

Preface 1. Introduction to AI FREE CHAPTER 2. Role of AI in CRM and Cloud Applications 3. Building Smarter Apps Using PredictionIO and Heroku 4. Product Recommendation Application using PredicitionIO and Salesforce App Cloud 5. Salesforce Einstein Vision 6. Building Applications Using Einstein Vision and Salesforce Force.com Platform 7. Einstein for Analytics Cloud 8. Einstein and Salesforce IoT Cloud Platform 9. Measuring and Testing the Accuracy of Einstein

Creating an administration app for creating and training dataset

Creating an administration application to create and train a dataset is breeze with the Salesforce platform, provided we have the Apex services written. We can invoke the Apex services we built for the creation of dataset and its training via either a process builder or an Apex. With the apex triggers, one will need to use @future (https://developer.salesforce.com/docs/atlas.en-us.apexcode.meta/apexcode/apex_invoking_future_methods.htm) annotated methods to invoke the web service calls or use batch or Scheduled apex.

For our admin application, we will use Apex (triggers and scheduled) to automate the sequence of operations we need to create and train a dataset.

The sequence for the application is as follows:

  1. An administrator creates a dataset record (dataset is a custom object) that will have a mandatory field of...
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