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  3. /Contrastive Learning
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Contrastive Learning

A self-supervised learning approach where the model learns by comparing similar and dissimilar pairs of examples.

Definition

A self-supervised learning approach where the model learns by comparing similar and dissimilar pairs of examples. It pulls representations of similar items closer together and pushes different items apart in the embedding space. The core idea behind models like CLIP and SimCLR.

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Related Terms

Self-Supervised Learning

A training approach where the model creates its own labels from the data itself.

CLIP

Contrastive Language-Image Pre-training.

Embedding

A dense numerical representation of data (words, images, etc.

Activation Function

A mathematical function applied to a neuron's output that introduces non-linearity into the network.

Adam Optimizer

An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.

AGI

Artificial General Intelligence.

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