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 ...

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.

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

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.

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 ...

The use of data and analytics at Colgate-Palmolive is grounded on the principle that investments in data and analytics must deliver measurable business value.

An important assumption shared by both DAGs and SWIGs is the necessity to identify all phenomena and measurements involved in the causal structure. To assess the variables requiring data collection to ...