How Numbers Station Combines LLM, RAG, and Domain Knowledge for AI-Driven Data Analysis
Offered By: Snorkel AI via YouTube
Course Description
Overview
Explore the innovative approach of Numbers Station in combining Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and domain knowledge for AI-driven data analysis in this 19-minute webinar excerpt from Snorkel AI. Learn how to leverage AI to extract valuable insights from your data by combining structured and unstructured information for a comprehensive view. Discover the power of multi-agent systems for tackling complex data analysis tasks and gain insights into building AI-powered data assistants capable of answering questions and providing actionable insights. Delve into the future of data analysis and uncover techniques to unlock the full potential of your data. For a more in-depth exploration, access the complete webinar through the provided link and explore additional GenAI project videos in the curated playlist.
Syllabus
How Numbers Station Combines LLM, RAG, and Domain Knowledge for AI-Driven Data Analysis
Taught by
Snorkel AI
Related Courses
Stanford Seminar - Failures & Where to Find Them: Considering Safety as a Function of StructureStanford University via YouTube Modeling Conceptual Understanding in Image Reference Games - CVPR 2020 Tutorial
Bolei Zhou via YouTube Multi-Agent Reinforcement Learning - Part II
Simons Institute via YouTube AI- From Algorithms to Ethics - ACM WomENcourage 2020
Association for Computing Machinery (ACM) via YouTube Python Reinforcement Learning using OpenAI Gymnasium – Full Course
freeCodeCamp