Graph databases open up views of interconnected data to help users discover and analyze relationships between datapoints, be it in customer transactions or internal operations. Knowledge graphs ...

Specialization: Data Science Foundations: Data Structures and Algorithms Instructor: Sriram Sankaranarayanan, Assistant Professor Prior knowledge needed: We highly recommended successfully completing ...

With the big data explosion, and the rise of NoSQL, something else started happening, too. Tools and databases for non-RDF graphs appeared in the market, and started finding success.

The four pillars of graph adoption This confluence of graph analytics, graph databases, graph data science, machine learning, and knowledge graphs is what makes graph a foundational technology.

Getting Your Data Graph-Ready After deciding on the technology and the key operational and logistical questions you want to answer with graph, your next step is to build a graph data model.

Our purpose is to bring together perspectives concerning the processing and use of statistical graphs to identify critical factors that appear to influence graph comprehension and to suggest ...

Richard M. Kubina Jr., Douglas E. Kostewicz, Kaitlyn M. Brennan, Seth A. King, A Critical Review of Line Graphs in Behavior Analytic Journals, Educational Psychology ...

DTSA 5511 Introduction to Deep Learning Same as CSCA 5642 Specialization: Machine Learning Instructor: Geena Kim, Assistant Teaching Professor Prior knowledge needed: Calculus, Linear algebra, Python ...