Latent Space
A compressed, learned representation space where similar data points are close together, used in autoencoders and VAEs.
Related Concepts
- Embedding: Explore how Embedding relates to Latent Space
- Representation Learning: Explore how Representation Learning relates to Latent Space
- Autoencoder: Explore how Autoencoder relates to Latent Space
- VAE: Explore how VAE relates to Latent Space
Why It Matters
Understanding Latent Space is crucial for anyone working with advanced concepts. This concept helps build a foundation for more advanced topics in AI and machine learning.
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This term is part of the comprehensive AI/ML glossary. Explore related terms to deepen your understanding of this interconnected field.
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Related Terms
Autoencoder
An unsupervised neural network that learns to compress data into a latent representation and reconstruct it, useful for dimensionality reduction.
Embedding
A dense vector representation of discrete data (words, tokens) in continuous space, capturing semantic relationships.
Representation Learning
Learning useful features or representations of data automatically, rather than hand-crafting them.