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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

Architecture and integration with applications

The architecture is well covered in the official documentation located at http://predictionio.incubator.apache.org/system/. However, we will expand on the important aspects a little more in this section so that we can completely understand the flexibility and the platform offering in detail.

The following diagram is from the official documentation of PredictionIO:

The key things to understand from the preceding diagram are as follows:

  • Event Server will provide a RESTful endpoint for all the applications to drop events in real time. For applications such as product recommender, events may include view data, for when a buyer views various products, an event when a buyer adds a product to a cart, an event from IOT devices, and so on. Event Server of the current version of PredictionIO can use PostgreSQL 9.1/MySQL 5.1 or Apache HBase...
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