A note from Udo Sglavo: When people ask me what makes SAS unique in the area of analytics, I will mention the breadth of our analytic portfolio at some stage. In this blog series, we looked at several essential components of our analytical ecosystem already. It is about time to
A good public transportation system is crucial to develop smart cities, particularly in great metropolitan areas. Network optimization algorithms can be applied to better understand urban mobility, particularly based on a multimodal public transportation network.
A note from Udo Sglavo: This post offers an introduction to complex optimization problems and the sophisticated algorithms SAS provides to solve them. In previous posts of this series, we learned that data availability, combined with more and cheaper computing power, creates an essential opportunity for decision-makers. After looking at network analytics
In this article, we summarize our SAS research paper on the application of reinforcement learning to monitor traffic control signals which was recently accepted to the 34th Conference on Neural Information Processing Systems (NeurIPS 2020), Vancouver, Canada. This annual conference is hosted by the Neural Information Processing Systems Foundation, a non-profit corporation that promotes the exchange of ideas in neural information processing systems across multiple disciplines.
This resource is designed primarily for beginner to intermediate data scientists or analysts who are interested in identifying and applying machine learning algorithms to address the problems of their interest. A typical question asked by a beginner, when facing a wide variety of machine learning algorithms, is “which algorithm should
All analytics projects have data as their foundation and this data is usually spread across a variety of databases, storage systems and locations. This diverse and complex landscape causes data scientists to spend an inordinate amount of time searching for the right data and preparing this information for analytics. It’s