The SAS Data Science Blog
Advanced analytics from SAS data scientists
Most computers can execute operations in parallel due to their multicore infrastructure. Performing more than one operation simultaneously has the potential to speed up most tasks and has many practical uses within the field of data science. SAS Viya offers several products that facilitate parallel task execution. Many of these
Decision trees are one of the top machine learning algorithms used by data scientists. Decision trees use supervised learning to classify problems. Even if you are not a data scientist, chances are you can interpret the visual output from a decision tree.
With the release of SAS Viya 2020.1.4, text categories and concept models can now be deployed into production with just a few clicks and used to score data in-batch and via API! You can also now use these models in decision flows.
Note from Gül Ege Sr. Director, Analytics R&D, IoT: The pattern of training in the Cloud, with your choices of framework and inferencing at the Edge with a target environment, are especially common in Internet of Things (IoT). In IoT, there is a proliferation of hardware environments on the Edge.
A few months ago, I published an article about network optimization and how to find an optimal tour when visiting multiple places of interest by using different types of transportation, like buses, trains, tram, metro, and even walking. For a real-world case, I decided to run these optimal tours in
In the second of two posts spotlighting SAS R&D innovators, SAS' Udo Sglavo interviews Chris Barefoot, Matthew Galati, Courtney Ambrozic and Davood Hajinezhad.