Getting started with vector databases and AI embeddings.

Format:

Video

Contributor:

Gabrieli, Idan, instructor.

Packt Publishing, publisher.

Language:

English

Subjects (All):

Support vector machines.

Machine learning.

Artificial intelligence.

Physical Description:

1 online resource (1 video file (1 hr., 59 min.)) : sound, color.

Edition:

[First edition].

Place of Publication:

[Birmingham, United Kingdom] : Packt Publishing, 2025.

Summary:

In this 2-hour course, you will learn how vectors, embeddings, and vector databases enable powerful AI-driven solutions. Covering fundamentals, workflows, and real-world use cases, this course helps beginners connect theory to practice in areas like semantic search, recommendation systems, and RAG. What I will be able to do after this course Understand how data is vectorized into embeddings Explore similarity metrics for comparing vector data Implement vector search workflows in practice Identify and evaluate vector database options Apply embeddings in RAG and recommendation systems Course Instructor(s) Idan Gabrieli has over a decade of experience in Israel's high-tech industry, collaborating with hundreds of companies He has published online courses since 2014, teaching thousands worldwide with a clear and structured approach Awarded as a top-rated instructor, Idan is recognized for simplifying complex topics into practical, engaging learning Who is it for? Designed for beginners in AI and data who want to understand embeddings and vector databases in practical terms Ideal for software developers, data professionals, and product managers aiming to explore modern AI-driven applications No advanced AI knowledge required, though basic familiarity with AI or LLM concepts is helpful.

Notes:

OCLC-licensed vendor bibliographic record.

ISBN:

1-80669-241-4

OCLC:

1539295804