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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
2.75 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.