With the recent global and regional socio-economic disruptions caused by the pandemic, industries such as retail, consumer products, manufacturing, pharmaceutical, and life sciences all struggle to align production and stocking with rapidly shifting purchasing demands. At the same time, some channels have surged ahead: online retailers, delivery services, and pharmacies are thriving. In this latest Data Science Central podcast, we discuss how injecting AI into existing business intelligence solutions can greatly enhance the ability of organizations to predict future demand for goods, even in uncertain and dynamic times.

Please Join this latest Data Science Central podcast to learn how you can develop machine learning models from an analytics base table and move that model to the edge for the purposes of scoring – or even training. Doing this will help you address latency reductions, security risks, and the potential for the corruption of your real time data. By improving models on the edge, your work will drive more data-driven business decisions faster.

Every organization wants to infuse the power of AI in its business. In this second of two parts we'll explore the productivity, performance and cost considerations that should be weighed when deploying deep learning at scale in the enterprise, and how to avoid the pitfalls of short-term decisions that can negatively impact your long term AI strategy.

In this latest Data Science Central podcast, we will continue to explore the hot topic of AI and Deep Learning at SAS. We will discuss how the SAS platform enables the development of AI applications and how SAS customers are using this exciting technology today.

In this latest Data Science Central podcast, we will introduce you to the hot topic of AI and Deep Learning at SAS. We will cover what is AI, what capabilities SAS offers, and how data scientists can leverage these deep learning capabilities.