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  3. /Representation Learning
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Representation Learning

The idea that useful AI comes from learning good internal representations of data.

Definition

The idea that useful AI comes from learning good internal representations of data. Instead of hand-crafting features, let the model discover them. Embeddings, latent spaces, and hidden layer activations are all learned representations. The quality of these representations largely determines model performance.

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Related Terms

Embedding

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

Feature Extraction

The process of identifying and pulling out the most important characteristics from raw data.

Deep Learning

A subset of machine learning that uses neural networks with many layers (hence 'deep') to learn complex patterns from large amounts of data.

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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