Manifold Hypothesis - AI & ML Glossary | Farez Vadsaria

Machine Learning Fundamentals

Manifold Hypothesis

The assumption that high-dimensional data lies on or near a lower-dimensional manifold, justifying dimensionality reduction.

This concept is essential for understanding machine learning fundamentals and forms a key part of modern AI systems.

Dimensionality Reduction
Representation Learning
Manifold Learning

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machine-learning-fundamentals dimensionality-reduction representation-learning manifold-learning

Related Terms

Dimensionality Reduction

Techniques to reduce the number of input features while preserving important information (PCA, t-SNE, autoencoders).

Representation Learning

Learning useful features or representations of data automatically, rather than hand-crafting them.

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