Redis + AI: Building a Vector Database with Redis
2h 32mIntermediate2024-07-31
Authors
Fernando Doglio
Published Author, Developer Advocate at OpenReplay
Course details
This course shows developers how to exploit the ready-made AI-related tools in Redis to build a vector database. Instructor Fernando Doglio starts with a look at structured versus unstructured data and AI-optimized databases, then jumps into Redis Enterprise to talk about how developers can use it as a vector DB. He also showcases examples like recommendation engines, semantic search, and others.
Skills covered
RedisMachine LearningArtificial Intelligence FoundationsDatabase DevelopmentDatabase ManagementArtificial Intelligence (AI)Open SourceSoftware DevelopmentOne-Off
Concepts
Introduction
- Introduction
- What you should know
Understanding Data
- What is structured data and where does it come from
- What is unstructured data and where does it come from
- Using structured data
- Using unstructured data - Use case examples
- Which is better Structured vs. unstructured data
- Unstructured to structured data
- Practical example - Metadata
AI-Optimized Databases
- What are AI-optimized databases
- What are vector databases
- What are embeddings
- How do vector databases work
- Examples of use cases for vector databases
Enter Redis
- Quick introduction of RediSearch and how to get it
- Redis used as a vector database
- Using Redis as a recommendation engine - Architecture overview
- Using Redis as a documentation retrieval database - Architecture review
Building an Image Similarity Search
- Introduction to the project to solve
- Architecture review - Using Redis as a vector database
- Tech stack overview
- Implementation overview - A deep dive into the main aspects of the implementation
Building a Semantic Search Example
- Introduction to the project to solve
- Architecture review - Using Redis as a vector database
- Tech stack overview
- Implementation video
Conclusion
- Next steps