Learning Salesforce Einstein

Overview of this book

Dreamforce 16 brought forth the latest addition to the Salesforce platform: an AI tool named Einstein. Einstein promises to provide users of all Salesforce applications with a powerful platform to help them gain deep insights into the data they work on. This book will introduce you to Einstein and help you integrate it into your respective business applications based on the Salesforce platform. We start off with an introduction to AI, then move on to look at how AI can make your CRM and apps smarter. Next, we discuss various out-of-the-box components added to sales, service, marketing, and community clouds from Salesforce to add Artificial Intelligence capabilities. Further on, we teach you how to use Heroku, PredictionIO, and the Force platform, along with Einstein, to build smarter apps. The core chapters focus on developer content and introduce PredictionIO and Salesforce Einstein Vision Services. We explore Einstein Predictive Vision Services, along with analytics cloud, the Einstein Data Discovery product, and IOT core concepts. Throughout the book, we also focus on how Einstein can be integrated into CRM and various clouds such as sales, services, marketing, and communities. By the end of the book, you will be able to embrace and leverage the power of Einstein, incorporating its functions to gain more knowledge. Salesforce developers will be introduced to the world of AI, while data scientists will gain insights into Salesforce’s various cloud offerings and how they can use Einstein’s capabilities and enhance applications.

Preface

What this book covers

What you need for this book

Free Chapter

Introduction to AI

Artificial Intelligence key terms

Programming languages used for machine learning

Practical machine learning with Google Prediction API and Salesforce

Summary

Role of AI in CRM and Cloud Applications

Sales Cloud Einstein offerings

Community Cloud Einstein features

Marketing Cloud Einstein features

Summary

Building Smarter Apps Using PredictionIO and Heroku

Introduction to PredictionIO

Architecture and integration with applications

Installation of PredictionIO

Getting started with PredictionIO

PredictionIO DASE components and customization of Engine

Summary

Product Recommendation Application using PredicitionIO and Salesforce App Cloud

Introduction to Spark MLlib

Setting up the Event Server app on Heroku

Setting up the Recommendation engine application on Heroku

Setting up IntelliJ IDEA IDE for customizing PredictionIO application

Introduction to building Lightning Component for App Cloud and Community Cloud

PredictionIO commands cheat sheet

Summary

Salesforce Einstein Vision

Signing up for Einstein Vision account

Explore Einstein Vision APIs

Set up the Heroku add-on for Einstein Vision Services

Building Node.js application using Einstein Vision on Heroku using React

Testing the application on localhost

Summary

Building Applications Using Einstein Vision and Salesforce Force.com Platform

Set up authorization between Salesforce and Einstein Vision APIs

Creating and training dataset via Apex

Creating an administration app for creating and training dataset

Creating Lightning Components to recognize image

Summary

Einstein for Analytics Cloud

Setting up Wave Analytics Cloud

Creating datasets, lenses, and dashboards

Using transformations to create dataset

Wave Analytics SAQL, XMD 2.0, and dataset Row-Level Security

Introduction to Einstein Data Discovery

Importing Salesforce data into Einstein Data Discovery and creating stories

Summary

Einstein and Salesforce IoT Cloud Platform

IoT Cloud key terms

IoT Cloud components

Apache Kafka on Heroku

IoT integration on the Salesforce Force.com platform

Using PredictionIO on IoT events

Summary

Measuring and Testing the Accuracy of Einstein

Measuring the accuracy of Sales Cloud Einstein

Building evaluation metrics for the PredictionIO systems

Measuring the accuracy of Salesforce Einstein Vision

Summary

Customer Reviews

5 star

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3 star

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1 star

What you need for this book

This book assumes that the reader is familiar with programming, either as an open source developer or a Salesforce developer.

Basic knowledge of Apex

The backend language for Salesforce applications is called Apex. It is a strongly-typed object-oriented language, which is syntactically very similar to Java.

Basic knowledge of Scala

PredictionIO is a Scala application, and hence familiarity with Scala will help you understand the code better. It is strongly recommended that you should try all the code covered in the book on your own local machine and try deploying the code on the Heroku free instance.

Basic knowledge of frontend technologies such as JavaScript and HTML

Salesforce Lightning components use web technology such as JavaScript and HTML, and hence having a basic knowledge will help you a great deal.

Salesforce Developer instances and MAC OS X

You will need a Mac OS X to locally test the code covered in Chapter 3, Building Smarter Apps Using PredictionIO and Heroku and Chapter 4, Product Recommendation Application Using PredicitionIO and Salesforce App Cloud. Also, it requires you to have your own Salesforce and Heroku instances. To obtain a free Salesforce instance, sign up at https://developer.salesforce.com/signup, and to obtain a free Heroku account, sign up at https://signup.heroku.com/.

To connect Mac OS X to Heroku, download and install the Heroku CLI from https://devcenter.heroku.com/articles/heroku-cli.

Learning Salesforce Einstein

Learning Salesforce Einstein

Overview of this book

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