With vector databases now powering business competitiveness through super-fast applications such as recommendation engines, it’s no surprise that the vector database market is set to grow 23% CAGR by 2032 (Markets and Markets).
Vector Search with Relational Databases using PostgreSQL
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Vector Search with Relational Databases using PostgreSQL
This course is part of Vector Database Fundamentals Specialization
Instructors: Skill-Up EdTech Team
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4.6
(14 reviews)
Intermediate level
Recommended experience
6 hours to complete
3 weeks at 2 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Describe the principles of modeling vector data in Relational databases (RDBMS).
Apply the commands necessary to store, retrieve, and query vectors efficiently in PostgreSQL.
Implement indexing techniques and optimization strategies for enhancing vector search performance.
Demonstrate, through hands-on labs, how to set up environments and perform vector searches using PostgreSQL.
Skills you'll gain
Details to know
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Recently updated!
June 2024
Assessments
3 assignments
Taught in English
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This course is part of the Vector Database Fundamentals Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There is 1 module in this course
Welcome to this module, where you’ll learn how to implement vector searches using relational databases. You’ll begin with a recap of RDBMS and then dive into the structures RDBMS uses to support vector data types and queries. You’ll apply what you know to perform similarity search tasks using special operators available in PostgreSQL. And, with a focus on PostgreSQL, you’ll learn how to create tsvector data, perform tsquery tasks, and perform bulk inserts using pg-vector for Node.js and psycopg2 for Python.
What's included
8 videos5 readings3 assignments6 app items5 plugins
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University of Colorado Boulder
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