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Deep Learning for Natural Language Processing Using Apache Spark and TensorFlow

Learn how Salesforce is using Apache Spark and TensorFlow to monitor customer activities in real-time and surface insights. Long Short-Term Memory (LSTM) networks have proven to be an effective technology to achieve state-of-the-art results on a variety of Natural Language Processing (NLP) tasks.


Low Touch Machine Learning

Leveraging your data to make better decisions is something every business wants to do, but doing it correctly involves weeks or months of work from highly skilled, hard to find individuals. However, many of the laborious steps a machine learning specialist follows in creating a custom application can be automated with enough compute power and flexibility. By leveraging Spark to do machine learning at scale, Salesforce Einstein has created a system that lets individuals with domain knowledge, but no machine learning expertise, create high quality, high impact machine learning applications.


Needle in the Haystack—User Behavior Anomaly Detection for Information Security

Salesforce recently invented and deployed a real-time, scalable, terabyte data-level and low false positive personalized anomaly detection system. Anomaly detection on user in-app behavior at terabyte-data scale is extremely challenging because traditional techniques like clustering methods suffer serious production performance issues.


How Switching to Apache Spark Improved Performance, Realizability, and Reduced Cost on a Very Large Scale ML Application

Krux, a Salesforce company, is a Data Management Platform (DMP) that helps its clients collect, manage, analyze and activate their people data. With a wide range of premium clients such as Kellogg, L’Oréal, Warner Brothers, New York Times, Washington Post, Uber, Spotify and many other household names, they see over 3.5 billion unique users globally a month, across sites, media, mobile app, transactional and offline traffic sources. That is more than Facebook, Wikipedia and Twitter combined.

Processing this scale of data volume and velocity has presented many challenges over the seven years Krux has existed, and they had to develop various proprietary strategies and technologies to overcome those. In this session, Salesforce shares how Apache Spark, in particular, helped transform the DMP’s data processing infrastructure, using as an example the evolution of their “Look-alike” algorithm.


Identifying Pricing Request Emails Using Apache Spark and Machine Learning

In this presentation, Sammy Nammari a Senior Machine Learning Engineer in the Intelligence team at SalesforceIQ explains how they process users' communication data (such as emails) to provide real time insights and recommended actions. Sammy specifically discusses how they use spark to build a machine learning model for identifying pricing-related emails from CRM customers