Embeddings Visualizer

About This Tool

The Embeddings Visualizer helps developers and data scientists understand and explore vector embeddings used in machine learning models. It provides interactive 2D and 3D visualizations of embedding spaces, allowing users to identify clusters, outliers, and relationships between data points. The tool is valuable for analyzing word embeddings, document vectors, and other high-dimensional representations.

Features

• Visualize vector embeddings in interactive 2D/3D space
• Apply dimensionality reduction techniques (t-SNE, UMAP, PCA)
• Compare similarity between vectors with distance metrics
• Cluster similar items and identify outliers
• Search for nearest neighbors to specific points
• Support for common embedding formats (Word2Vec, GloVe, BERT, etc.)
• Customize visualization with colors, labels, and animations
• Export visualizations for presentations and documentation