Similarity Search Courses and Certifications

James Briggs

FAISS - Introduction to Similarity Search

Explore efficient similarity search with Facebook AI Similarity Search (FAISS). Learn implementation, options, and how FAISS enhances semantic search speed.

• YouTube
• 32 minutes
• On-Demand
• Free Video

James Briggs

Traditional Methods for Similarity Search - Jaccard, W-Shingling, Levenshtein

Explore three traditional similarity search methods: Jaccard Similarity, w-shingling, and Levenshtein distance. Learn their applications in language comparison and document matching for effective search engines.

• YouTube
• 25 minutes
• On-Demand
• Free Video

James Briggs

IndexLSH for Fast Similarity Search in Faiss

Explore fast similarity search using IndexLSH in Faiss. Learn efficient implementation techniques for large-scale data retrieval and comparison in AI applications.

• YouTube
• 19 minutes
• On-Demand
• Free Video

James Briggs

Choosing Indexes for Similarity Search - Faiss in Python

Explore Faiss indexes for efficient similarity search, comparing Flat, LSH, HNSW, and IVF to optimize performance in large-scale datasets. Learn to choose and implement the best index for your needs.

• YouTube
• 32 minutes
• On-Demand
• Free Video

Simons Institute

A Bi-metric Framework for Fast Similarity Search

Explore a novel bi-metric framework for efficient nearest neighbor search, combining accurate but costly ground-truth metrics with faster proxy metrics to optimize data structures and query procedures.

• YouTube
• 38 minutes
• On-Demand
• Free Video

Data Science Conference

Similarity Search - Taking Your Search Engine to the Next Level

Dive into advanced similarity search techniques and AWS services for enhancing search engine capabilities, understanding observability, monitoring, and telemetry implementation.

• YouTube
• 26 minutes
• On-Demand
• Free Video

MLOps World: Machine Learning in Production

Personalized Recommendations and Search with Retrieval and Ranking at Scale - Hopsworks Workshop

Implement personalized recommendations using retrieval and ranking architecture with two-tower embedding models. Learn offline and online infrastructure for scalable, low-latency systems on Hopsworks platform.

• YouTube
• 2 hours 1 minute
• On-Demand
• Free Video

Qdrant - Vector Database & Search Engine

Getting Started with Qdrant - Introduction to Vector Database and Similarity Search

Master vector similarity search using Qdrant to build semantic search and recommendation systems through hands-on practice with sample datasets and practical implementations.

• YouTube
• 24 minutes
• On-Demand
• Free Video

Learn RAG

Learn how to improve the accuracy and reliability of LLM-based apps by implementing Retrieval-augmented Generation (RAG) using embeddings and a vector database.

• Scrimba
• 1 hour 34 minutes
• On-Demand
• Free Online Course

Qdrant - Vector Database & Search Engine

Natural Language Processing with Qdrant for Vector Similarity Search

Master vector similarity search using Qdrant to create embeddings from text data, perform contextual searches, and build recommendation systems for enhanced natural language processing applications.

• YouTube
• 43 minutes
• On-Demand
• Free Video

Qdrant - Vector Database & Search Engine

Embeddings and Similarity Search with Qdrant Vector Database

Explore vector embeddings and similarity search concepts through hands-on demonstrations using Qdrant database, with practical examples for implementing efficient search solutions.

• YouTube
• 12 minutes
• On-Demand
• Free Video

DigitalSreeni

Understanding FAISS for Efficient Similarity Search of Dense Vectors

Discover how FAISS library enables fast similarity search and clustering of dense vectors, focusing on IndexFlatL2 and IndexIVF approaches for optimized vector matching and clustering.

• YouTube
• 26 minutes
• On-Demand
• Free Video

Document Processing and Retrieval with LangChain in Python

Unlock the power of document intelligence with LangChain in Python, learning to load, split, embed documents and perform similarity searches to extract relevant insights.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Document Processing and Retrieval with LangChainGo

Unlock document intelligence with LangChainGo by loading, splitting, embedding documents and performing similarity searches to create context-aware AI responses.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate

Document Processing and Retrieval with LangChain in Java

Master document processing and retrieval using LangChain in Java. Build skills in loading, splitting, embedding documents and performing similarity searches for intelligent applications.

• CodeSignal
• 2 hours
• On-Demand
• Free Certificate