Vector Databases: from Embeddings to Applications

Name: Vector Databases: from Embeddings to Applications
Rating: 4.6 (12 reviews)

Coursera · intermediate · 1h

★ 4.612 reviewsPrice on site

Vector databases play a pivotal role across various fields, such as natural language processing, image recognition, recommender systems and semantic search, and have gained more importance with the growing adoption of LLMs. These databases are exceptionally valuable as they provide LLMs with access to real-time proprietary data, enabling the development of Retrieval Augmented Generation (RAG) applications.

Skills covered

RAG NLP Vector Databases Large Language Models Embeddings LLM Application Large Language Modeling Retrieval-Augmented Generation Algorithms Semantic Web

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