This session will delve into the exciting world of Retrieval Augmented Generation (RAG) and Large Language Models (LLMs). I'll cover:
• Core Concepts: A concise overview of RAG and LLMs, including their key components, architectures, and use cases.
• Open-Source Frameworks
• Best Practices
• Real-World Applications
• The Future of RAG & LLMs

Key Takeaways:
• A solid understanding of RAG and LLM fundamentals and their applications.
• Knowledge of key open-source frameworks and their capabilities.
• Practical guidance on building and deploying effective RAG and LLM systems.
• Insights into the future of RAG and LLM technologies.
Target Audience:
• Developers
• Data Scientists
• Machine Learning Engineers
• Researchers
• Anyone interested in AI and machine learning