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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

Product Recommendation Application using PredicitionIO and Salesforce App Cloud

In Chapter 3, Building Smarter Apps Using PredictionIO and Heroku, we covered the basics of the DASE model of PredictionIO and learned how one can deploy the PredictionIO engine code and Event Server using the Heroku Buildpack. In this chapter, we will focus on building a complete Recommendation engine that suggests similar products for a given product based on user View events using PredictionIO. We will host the Event Server endpoints and the Engine Application written in Scala on the free Heroku version. We won't be using the Heroku Buildpack for this working code as Buildpack uses paid Performance Editions of Heroku (Buildpack automates the training of a model during runtime and is recommended for a production-based application), and instead, we will train the model via the command-line interface...

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