Glossary › Representation

Embedding

Dense vector representation of text/images in continuous space where similar items are nearby. Produced by encoder models. Dimensions: 384-3072. Used for search, clustering, classification.

Where this is taught

• Embedding Models — The 2026 Deep Dive — Phase 3: Transformers for NLP
• Debugging Retrieval Quality — Phase 3: Enterprise RAG Systems
• Embeddings & Semantic Search — Phase 0: LLM Fast Track
• Image Retrieval & Metric Learning — Phase 3: Generative Vision Models
• Multi-Token Prediction (MTP) — Phase 4: Training LLMs
• Performance Optimization & Scaling — Phase 8: Production Hardening & Operations

Related terms

Vector Store · Cosine Similarity · Semantic Search

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