Deep Learning

In Deep Learning, the neural network has multiple layers. At the top layer, 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.

Deep Learning has increased in popularity because it has proven to outperform other methodologies for machine learning. Due to the advancement of distributed computing resources and businesses generating an influx of image, text, and voice data, Deep Learning can deliver insights that weren’t previously possible.

Consider the following diagram:

From an example from the U.S. government report, in an image recognition application, a first layer of units might combine the raw data of the image to recognize simple patterns in the image; a second layer of units might combine the results of the first layer to recognize patterns of patterns; a third layer might combine the results of the second layer, and so on. We train neural networks by feeding them lots of delicious big data to learn from.

Salesforce Einstein offers Predictive Vision Services (currently in Pilot) for training and solving image recognition use cases. We will discuss in detail how to use these services to bring the power of image recognition to the CRM apps.