UPCOMING Training "Structuring Healthcare Data for usage with LLMs"
Date: 16th October 2024 | Time: 9am PT/ 12pm ET/ 4pm GMT
Duration: 2 Hours, October 16th, 12 PM ET
AI Platform Specialist Solution Architect | Red Hat
Principal Specialist Solution Architect | Red Hat
Why is Structuring Healthcare Data so important when creating a Healthcare LLM?
Discuss RAG Architecture for a future Healthcare LLM and/or Chatbot.
What does Unstructured.io do?
Why do we use a Vector Database?
Steps to structuring our data for usage!
Storing our structured data in Weaviate.
Querying our newly structured healthcare data.
Structuring healthcare data (for Chatbot usage) is hard, but it is made easier by using data curation tools (such as Unstructured.io) and RAG.
Vector Databases are key to creating a useful LLM. The success of your LLM (or Chatbot) is directly related to the ‘curation’ of your data set.
Be smart about where (or if) you should move your data for curation and usage. Sometimes curating your data in place, then moving your vector database elsewhere is a good cost savings decision.
Beginner knowledge of Kubernetes (or OpenShift), Python, Generative AI and database principals.
No medical healthcare data knowledge is necessary.