Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

YouTube

Natural Language Processing with Qdrant for Vector Similarity Search

Qdrant - Vector Database & Search Engine via YouTube

Overview

Learn how to leverage Qdrant for text-based vector similarity search in this 43-minute tutorial that demonstrates creating vector embeddings from text data, implementing similarity search functionality, and building context-based recommendation systems. Explore practical examples of adding embeddings to Qdrant's vector database, performing efficient similarity searches, and generating recommendations based on document context within a corpus. Access hands-on implementation details through the provided GitHub repository and comprehensive documentation on the Qdrant website.

Syllabus

Natural Language Processing with Qdrant for Vector Similarity Search

Taught by

Qdrant - Vector Database & Search Engine

Reviews

Start your review of Natural Language Processing with Qdrant for Vector Similarity Search

Never Stop Learning.

Get personalized course recommendations, track subjects and courses with reminders, and more.

Someone learning on their laptop while sitting on the floor.