On-demand webinar
Elasticsearch AI Workshop with Microsoft: Craft Generative AI Applications
Leverage the power of the Azure OpenAI LLM on your private data, at scale, securely, and cost-effectively.
Hosted by:
Susan Shu Chang
Principal Data Scientist
Elastic
Francesco Di Stefano
Principal Solutions Architect
Elastic
Greg Crist
Principal Solutions Architect
Elastic
Overview
This brief workshop, powered by Microsoft and Elastic, will spotlight Elasticsearch as a vector database, offering an introduction to Elasticsearch, RAG, and generative AI. Participants will gain hands-on experience in indexing, searching, and analyzing data with Elasticsearch. Additionally, they'll learn to leverage transformer models for generating embeddings and semantic search. The workshop covers running transformer models locally, optimizing download caching for a smaller LLM to expedite development and training, and techniques for chunking data, generating embeddings, and executing semantic search within Elasticsearch.
Who should attend this workshop?
This workshop is ideal for anyone who wants to go hands-on with Elasticsearch and learn how to use it to search and analyze data. No prior experience with Elasticsearch is required.
What will you learn?
- How to index, search, and analyze data using Elasticsearch
- How to use transformer models to generate embeddings and perform semantic search
- How to use GitHub Codespaces to run transformer models locally
- How to cache the download of a smaller LLM
Prerequisites
- A basic understanding of Python programming
- Access to GitHub Codespaces
Materials
- Laptop with internet access
- Access to GitHub Codespaces
Benefits of attending
- Gain a hands-on understanding of Elasticsearch
- Learn how to use transformer models to generate embeddings and perform semantic search
- Learn how to run transformer models locally
- Network with other Elasticsearch users and experts
Excited about AI in search and like to get started, visit our listing on Azure Marketplace.
Additional resources
Register to watch
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