triplet

The term “triplet” refers to a specific method in machine learning for training models to recognize similarities and differences. The underlying method involves using three pieces of data at a time: an anchor, a positive example (similar to the anchor), and a negative example (dissimilar to the anchor),

Citations:

[1] https://www.v7labs.com/blog/triplet-loss

[2] https://deepchecks.com/glossary/triplet-loss/

[3] https://www.orbussoftware.com/resources/blog/detail/the-triple-threat-how-digital-triplets-are-disrupting-traditional-business-models

[4] https://machinelearning.wtf/terms/triplet-loss/

[5] https://en.wikipedia.org/wiki/Triplet_loss

[6] https://www.linkedin.com/pulse/triple-threat-how-digital-triplets-disrupting-traditional

[7] https://towardsdatascience.com/triplet-loss-advanced-intro-49a07b7d8905

[8] https://studentsxstudents.com/ai-workloads-for-dummies-9c472d3c58d?gi=baf2126df0aa

[9] https://news.ycombinator.com/item?id=28736405