Industrial Use Case of Neural Networks : Salesforce

3 min readMar 4, 2021

Content of this blog

Neural networks, also known as artificial neural networks (ANNs) or simulated neural networks (SNNs), are a subset of machine learning and are at the heart of deep learning algorithms.
Their name and structure are inspired by the human brain, mimicking the way that biological neurons signal to one another.
Artificial neural networks (ANNs) are comprised of a node layers, containing an input layer, one or more hidden layers, and an output layer. Each node, or artificial neuron, connects to another and has an associated weight and threshold.
If the output of any individual node is above the specified threshold value, that node is activated, sending data to the next layer of the network. Otherwise, no data is passed along to the next layer of the network.

About Salesforce

Salesforce is a software company that was founded by Marc Benioff in 1999. Salesforce’s core business focuses on Customer Relationship Management (CRM) software solutions.
Companies, and salespeople in particular, typically rely on CRM tools to help them manage their entire the sales process, from customer sourcing to suggested next steps and pipeline management.
In recent years, machine learning has become a paramount technology for CRM products, and Salesforce is currently working on implementing an innovative machine learning strategy to fuel its future growth.

Einstein : Salesforce’s approach towards neural networks

Salesforce Einstein is a set of advanced AI capabilities that help users get smarter insights from their data in order to deliver personalized customer experience, get proactive recommendations for the next best actions, and automate routine tasks.
Einstein analyzes the historical data against set parameters and creates data models that are further trained on huge data sets. When fresh data comes in, Einstein double-checks whether the previously created operational models are still accurate, and updates them in case they’re outdated. This way, Einstein-based predictions and recommendations always stay up-to-date.

Einstein’s Benefits

User-readiness : Works seamlessly within Salesforce processes
No need for data science expertise : Does all the heavy lifting of data processing modelling
Custom-friendliness : Provides service that could be customized by coding for advanced customization
Accurate data models : Checks whether the created data models are adequate and updated at all times
Automation : Automates manual data entry as well as workflows based on predictive analysis