Learn to Love Working with Vector Embeddings
Unlock the power of machine learning. Our guides will help you conquer vector embeddings and build better applications.
Algorithms & Libraries
Facebook AI Similarity Search (Faiss): The Missing Manual
Filtering: The Missing WHERE Clause in Vector Search
Hierarchical Navigable Small Worlds (HNSW)
Locality Sensitive Hashing (LSH)
Nearest Neighbor Indexes for Similarity Search
Product Quantization
Random Projection for Locality Sensitive Hashing
Semantic Search: Measuring Meaning From Jaccard to Bert
Composite Indexes and the Faiss Index Factory
Transformers Are All You Need
Ludicrous BERT Search Speeds
Applications of Vector Search
NLP for Semantic Search
Dense Vectors
Sentence Embeddings and Transformers
Training Sentence Transformers with Softmax Loss
Training Sentence Transformers with Multiple Negatives Ranking Loss
Multilingual Sentence Transformers
Question Answering
Unsupervised Training for Sentence Transformers
Vector Search 101
What is Vector Similarity Search?
What are Vector Embeddings?
What is a Vector Database?
Vector Search for Developers: A Gentle Introduction
Vector Search News
What will you build?
Upgrade your search or recommendation systems with just a few lines of code, or contact us for help.