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Course

Multimodal Data: In Focus

A lot of our world is multimodal. Learn how to work with multimodal data, combining the right embedding and generative models with Weaviate.

Level
Intermediate
Duration
2 hour(s)
Learning Paths

What you'll be able to do:

  • •
    Create a local instance of Weaviate with a multimodal vectorizer module
  • •
    Produce, store and index multimodal data
  • •
    Perform multimodal searches
  • •
    Use generative AI models to augment and transform retrieved data

Prerequisites:

wa050-py

Course Content

1

Weaviate for multimodal data

Create a Weaviate instance for multimodal data.

2

Populate the database

Create a collection and import data, and have Weaviate create vectors for you.

3

Perform searches

Learn how to use search functions in Weaviate.

4

LLMs and Weaviate (RAG)

Use generative AI models to augment and transform retrieved data.