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- Qdrant Vector Space Training Workshop
Qdrant Vector Space Training Workshop
데이터베이스
개발자
AWS GenAI Loft | 샌프란시스코
생성형 AI
산업
혁신
기계 학습
현대적 애플리케이션
네트워킹
이벤트 사이트
During this one-day event, you’ll learn how to build a Retrieval-Augmented Generation (RAG) recommendation engine specifically designed to enhance meeting productivity. By leveraging the transcription SDK, you'll create a system that recommends future meetings to attend based on missed content—ensuring you stay connected to topics of interest.
Please note that attendees require a photo ID to enter the venue.
The Qdrant team, in cooperation with AWS, invites you to our first Vector Space Training Workshop event at the AWS AI Engineering Loft where we will show you hands on how to build a state of the art RAG application.
Qdrant is an industry-leading vector database and a semantic search engine, powering large operations such as Twitter, Discord, Firefox, Tripadvisor, Johnson & Johnson, Deloitte, and more.
During this one-day event, you’ll learn how to build a Retrieval-Augmented Generation (RAG) recommendation engine specifically designed to enhance meeting productivity.
By leveraging the transcription SDK, you'll create a system that recommends future meetings to attend based on missed content—ensuring you stay connected to topics of interest.
Agenda:
- 9:00 AM - Doors Open
- 9:30-10:00 AM - Networking + Breakfast
- 10:00-12:00 PM - Workshop: Building the RAG App
- 12:00-1:00 PM - Lunch Break
- 1:00-3:00 PM - Hands-on Lab: Fine-tuning and Testing
- 3:00-3:30 PM - Q&A Session
- 3:00-4:00 PM - Panel
Learning Objectives:
- Understand the fundamentals of RAG and its application in meeting recommendations.
- Gain practical experience using the transcription SDK to build a custom RAG recommendation engine.
- Learn how to fine-tune models to improve the relevance and accuracy of recommendations.
Key Topics:
- Introduction to RAG:
- Overview of RAG and its benefits in recommendation systems.
- Transcription SDK:
- Step-by-step guide on integrating and utilizing the transcription SDK.
- Building the Engine:
- Best practices for developing a recommendation engine that analyzes missed meetings.
- Model Fine-Tuning:
- Techniques for enhancing recommendation accuracy based on user preferences and meeting content.
Target Audience:
This workshop is designed for developers, data scientists, and AI practitioners interested in building practical AI applications for improving meeting effectiveness.
Hosts:
- Zoom Team
- Qdrant Team
- LlamaIndex Team
- Anthropic Team