When it comes to providing reliable, flexible, and efficient object persistence for software systems, today's designers and architects are faced with many choices. From the technological perspective, ...
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The Hidden Variable in AI Success: Why Data Quality Trumps Model Size
The conversation about artificial intelligence typically orbits around model architecture, parameter counts, and ...
The intersection of the COVID-19 pandemic and analytics has been in focus almost since the pandemic began. Organizations like Johns Hopkins Center for Systems Science and Engineering (CSSE), the New ...
Getting the “Business” into Business-Oriented Data Modeling – Practical Techniques & Examples by Alec Sharp This white paper by industry expert Alec Sharp illustrates these points and provides ...
Data modeling is the process of defining datapoints and structures at a detailed or abstract level to communicate information about the data shape, content, and relationships to target audiences.
The Phi-4 model was trained on just 1.4 million carefully chosen prompt-response pairs. Instead of brute force, the Microsoft Phi-4 research team focused on “teachable” examples at the edge of the ...
How to use Excel’s Data Model to turn related data into meaningful information Your email has been sent Excel's Data Model feature allows you to build relationships between data sets for easier ...
Data Matching to Support Analysis of Cancer Epidemiology Among Veterans Compared With Non-Veteran Populations—An Exemplar in Brain Tumors Real world data (RWD) were from the Flatiron Health advanced ...
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