Few-Shot Learning is a learning approach in which a model is trained to identify new classes with only a few labeled instances, replicating the capacity to generalize to new concepts with little data.
Few-Shot Learning
SHARE
Related Links
A CMO recently asked me a deceptively simple question: “If we gave an AI agent full…
I once watched a campaign manager juggle ten tools, fifteen stakeholders, and a spreadsheet that looked…