All Times EDT
Keywords: SAS, Data Science, Open Source, Python, R, Machine Learning, Artificial Intelligence, Data Mining, Visualization, Big Data, Software, Academia, Teaching, Learning, Statistics, Computer Science, Industry, Career
Machine Learning, Artificial Intelligence, Deep Learning, Computer Vision, Natural Language Processing, Data Mining…the vocabulary of data science continues to expand at such a staggering rate, the data scientist might feel overwhelmed and forced to choose. However, it’s no longer viable to draw a line in the sand with proprietary software on one side and open source technologies on the other: data scientists need to move quickly and with confidence across a variety of conventions to utilize the entire toolkit. SAS Viya synthesizes an entire technology stack within a scalable framework that leverages the robustness of proprietary tools and integrates the experimentation of open source to deliver these technologies to users across a variety of skill levels. Within the SAS Platform, data scientists have open access to a distributed in-memory architecture that can be accessed from an interactive visual perspective, via an auditable workflow approach, within a supportive proprietary coding interface, and from an open source notebook application using an R or Python syntax. From descriptive statistics to predictive analytics to AI and machine learning, SAS Viya provides valuable career skill as it facilitates classroom learning. This session will demonstrate how SAS Viya unifies data scientists across an integrated interface and incorporates open source so you no longer have to be on either side of the open source debate.