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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 and training dataset via Apex

In Chapter 5, Salesforce Einstein Vision, we trained the dataset using CURL. We zipped all the images in our local drive and then used the CURL command to create the dataset from the .zip file asynchronously.

Currently, Einstein supports the creation of a dataset via three major APIs:

  • Creating a dataset from a zip file synchronously
  • Creating a dataset from a zip file asynchronously
  • Creating a new dataset and labels, if they're specified

To derive better and more efficient performance, the docs refer to creating dataset from a zip file asynchronously, and hence for rest of the chapter, as a recommended practice, we will be using asynchronous creation of dataset from the zip file.

For data storage, we will leverage the free version of Cloudinary (https://cloudinary.com/). The primary reason to store the files used for training in a cloud...

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