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.
Fine-tuning is the process of optimizing a pre-trained model for a specific task. This method is an important part of the approach known as transfer learning and is widely used in modern artificial intelligence projects.
The data lake is where long-term data containers gather that capture, clean, and explore any raw data format at scale. Data subsets are powered by low-cost technologies that many downstream possibilities can benefit from, including data warehouses, and recommendation engines.
Data governance ensures that your data is consistent, reliable, accurate, and trusted in data-driven retrieval processes.
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