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What is Contrastive Learning?

Contrastive Learning is a machine learning technique where the model learns by comparing similar and dissimilar examples to understand what makes things alike or different. A model is trained to put similar items (like two photos of cats) closer together in its internal representation while move dissimilar items (like a photo of a cat and a photo of a toaster) farther apart.

Contrastive Learning mentioned at Stanford HAI

What is Contrastive Learning? | Stanford HAI

Explore Similar Terms:

Self-Supervised Learning | Unsupervised Learning | Embeddings

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