Connectivity analytics is an emerging discipline that helps to explore the interrelated connections and effects between people, products, processes, machines, and systems within a network by mapping these connections and continuously monitoring the interactions between them. For example, the influence of opinion leaders has been used to answer difficult and persistent business questions about temporal relationships between nodes in the assessment of external event or actors on financial risk and network performance evaluation.
Feature Engineering is one of the most labor-intensive and creative phases of the machine learning process. This process involves the transformation of raw data into more meaningful and processable properties. The basic principles of Feature Engineering include using domain knowledge, data discovery, understanding the nature of data, and problem-oriented thinking.
Foundation Models (FMs) refer to structures trained on large data sets in the field of artificial intelligence and machine learning, versatile and usable in a variety of applications.
Digital citizenship is a concept that refers to individuals behaving ethically, responsibly and safely in the digital world (internet, social media, mobile devices).
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