Attend this session during the SAS Explore event on Sept 27-29 or view the recording at your convenience. We will showcase the use of SAS Intelligent Decisioning, SAS Model Manager, and SAS Visual Analytics on the SAS Viya platform for a solution that helps mitigate inequitable credit decisions.
SAS' Gunce Walton introduces to you a new scoring capability, how it utilizes Deep Neural Networks (DNNs) and shares use cases with PROC DEEPCAUSAL.
The IEEE Visual Analytics Science and Technology (VAST) Challenge provides a great opportunity to validate our software against real-world scenarios using complex data sets. Not only do we learn from these projects, but we also send feedback to our development teams to further improve product capabilities for customers.
SAS' Damian Herrick chronicles the refresh of a 2002 social-network analysis aimed at identifying influential peer educators among former drug users.
Let's create a Multi-stage Computer Vision model to detect objects on high-resolution imagery taken from an aerial view. The goal is to locate a dog and determine if he is wearing a scarf or not and what color the scarf is.
In this introduction to powerful knowledge graph tools, SAS' Brandon Reese shows you how they can predict disease similarity and compound similarity using an unsupervised approach.
SAS' Bahar Biller reveals how simulations enable KPI generation, risk quantification, risk management and more.
Wouldn’t it be cool if we establish a mechanism that provides more data scientists easy access to SAS Reinforcement Learning capabilities, from a centralized location and using a standardized approach?
SAS research statistician Ji Shen reveals how to train a machine to be a batting coach.
SAS' Michael Lamm gives an overview of Bayesian Additive Regression Trees (BART) and demonstrates training and scoring BART models in SAS Visual Statistics.
