Finding the next step…
piatra . institutepathwayspiatra . institutepathwaysFinding the next step…
A benchmark score evaluates a particular task and dataset, not every use of a deployed system.
Try the short introduction first, or bring equivalent reading experience. Obtain the specified text before beginning the longer reading.
Design a small image-classification benchmark and list two deployment questions that accuracy alone would not answer.
Start here if the background is new. Equivalent experience is enough.
Introduces the question and vocabulary used in the longer selected reading.
Fei-Fei Li · book
Introduction or preface and opening chapter. Record the edition and translator before reading.
Library or purchase
Find a copyThe Worlds I See. Computer vision and human-centred approaches to AI. Study the relationship among a dataset, a benchmark and the people affected by a system.
Answer this question in your own words: What does a vision benchmark leave outside its score?
Name the claim, then explain why a reader might accept it.
A benchmark score evaluates a particular task and dataset, not every use of a deployed system.
What to look for
Common mistake: Summarising a biography instead of explaining the argument.
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Fei-Fei Li · book
Locate two passages about “What does a vision benchmark leave outside its score” using the contents or index. Record their chapter/section names in your notes; this route assigns selections, not the whole work.
Library or purchase
Find a copyThe Worlds I See. Computer vision and human-centred approaches to AI. Study the relationship among a dataset, a benchmark and the people affected by a system.
What would make your activity a convincing example?
Design a small image-classification benchmark and list two deployment questions that accuracy alone would not answer.
A useful response carries out the task: Design a small image-classification benchmark and list two deployment questions that accuracy alone would not answer. It records the observation or passage used and explains how it bears on the question.
What to look for
Common mistake: Presenting an opinion without showing the example it rests on.
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What is one conclusion this reading does not establish?
Test the boundary: Keep a research result, an autobiographical account and a policy position distinct.
Keep a research result, an autobiographical account and a policy position distinct.
What to look for
Common mistake: Treating a useful interpretation as an unrestricted fact.
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Background, different viewpoints, and further reading.
Computer vision and human-centred approaches to AI. Study the relationship among a dataset, a benchmark and the people affected by a system.
Introduction or preface and opening chapter. Record the edition and translator before reading.