Machine learning on data without labels — the model finds patterns and structure on its own.
Machine learning on data without labels — the model finds patterns and structure on its own. Clustering, anomaly detection, and dimensionality reduction are unsupervised tasks. Pre-training language models on raw text is technically self-supervised, a specific form that creates its own supervisory signal.
A training approach where the model creates its own labels from the data itself.
A branch of AI where systems learn patterns from data instead of following explicitly programmed rules.
A mathematical function applied to a neuron's output that introduces non-linearity into the network.
An optimization algorithm that combines the best parts of two other methods — AdaGrad and RMSProp.
Artificial General Intelligence.
The research field focused on making sure AI systems do what humans actually want them to do.
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