Embedding Visualizer
Visualize text embeddings in 2D/3D space using PCA or UMAP
PCA Visualization (2D)
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Text Items (10)
Machine learning is amazing
Deep learning uses neural networks
I love pizza and pasta
Italian food is delicious
Python is a programming language
JavaScript is used for web development
The weather is sunny today
It's raining outside
Artificial intelligence will change the world
AI models can generate text
About
PCA (Principal Component Analysis) finds the directions of maximum variance in high-dimensional data.
UMAP (Uniform Manifold Approximation) preserves local and global structure better than PCA.
Note: This demo uses simulated embeddings. In production, use real embedding models like OpenAI, Cohere, or sentence-transformers.