After a cuGraph importance pass, a city food-bank warehouse wants those scores as extra columns on the original product table for later exploratory analysis. What should they do?
Select an answer to reveal the explanation.
Short Explanation
cuGraph importance scores should come back as extra columns on the product table. Join those graph-derived fields into a cuDF frame so the metrics become data. Do not discard the table for an LLM prompt, serve the scores, or print them from a kernel.
Full Explanation
Graph analytics can produce data: metrics become columns on a RAPIDS table. Joining cuGraph importance scores back into a cuDF product frame is that step. It is not an experiment that feeds graph features to an LLM, and it is not a serving call. Keep the metrics on the table for later EDA.