It can bring the power of image recognition to CRM and third-party applications so that end users across sales, service, and marketing can discover new insights about their customers and predict outcomes that lead to smarter decisions.

1. Ceptes R&D
Chandan
Mobin
Gowthami
Jagadeesh
Vijay
Prateek

2. Salesforce Einstein Vision By Chandan Panigrahy
Contents
● Prerequisite knowledge on AI
○ Introduction to AI
○ Goals of AI
○ Machine Learning
○ Deep Learning
● Einstein Vision
○ Introduction
○ Einstein Vision
○ Einstein Vision Terminology

3. Introduction to AI
The science and engineering of making intelligent machines, especially intelligent computer programs.
- John McCarthy (Father of AI)
Goals of AI -
● To Create expert systems
● To implement human intelligence in machines

4. Basic Terminologies of AI
Machine Learning - Machine learning is a type of AI that provides computers with the ability to learn
without being explicitly programmed.
Neural Network - A neural network is a set of algorithms designed to recognize patterns.
Deep Learning - Deep learning is a branch of machine learning, where we create and train a neural
network in a specific way.
Layer structure of Deep Learning:
● Top Layer: here the network trains on a specific set of features and then sends that information to
the next layer
● The network takes that information, combines it with other features and passes it to the next layer,
and so on.

5. Layer Structure of Deep Learning -

7. Einstein Vision
Introduction -
It can bring the power of image recognition to CRM and third-party applications so that end users across
sales, service, and marketing can discover new insights about their customers and predict outcomes that
lead to smarter decisions.
Einstein Vision -
It contains a new set of APIs that will bring deep learning to developers with Predictive Vision Services,
which classify unstructured images against a library of pre-trained classifiers.
Where we use -
Visual search — Expand the ways that your customers can discover your products and increase sales.
Brand detection — Monitor your brand across all your channels to increase your marketing reach and
preserve brand integrity.
Product identification — Increase the ways that you can identify your products to streamline sales
processes and customer service.

8. Einstein Vision Terminology
1. Dataset - The training data, which consists of inputs and outputs.
2. Label - A group of similar data inputs in a dataset that your model is trained to recognize. Label
references the output name you want your model to predict.
3. Model - The model predicts which class a new input falls into based on the predefined classes
specified in your training dataset.
4. Training - The process through which a model is created and learns the classification rules based on
a given set of training inputs (dataset).
5. Prediction - The results that the model returns as to how closely the input matches data in the
dataset.

10. Thank You...