Multimodal RAG Text Images Tables amp Audio Pipeline

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Explore multimodal Retrieval-Augmented Generation (RAG) with this comprehensive video. • Learn how to build an end-to-end RAG pipeline that handles text, images, graphs, tables, and audio data using Weaviate as a vector database. • This video covers everything from data collection to system testing, with a focus on ESG and Finance applications. Perfect for AI engineers, data scientists, and machine learning enthusiasts looking to expand their skills in building versatile and powerful RAG systems. • ℹ️ CHAPTERS OF THE VIDEO • 0:00 - Introduction • 0:53 - Overview of Multimodal RAG • 5:50 - Text, Images, Tables, and Audio Data Collection Preprocessing • 41:34 - Set Up Weaviate • 49:40 - Data Ingestion into Weaviate • 54:21 - Implementing the Retriever Component • 58:47 - Building the Augmented Generation Component • 01:03:41 - Testing and Optimizing the RAG System • 01:09:42 - Clean Workspace • 01:09:54 - Conclusion and Next Steps • Code: https://github.com/keitazoumana/multi... • Connect: • Medium:   / zoumanakeita   • LinkedIn:   / zoumana-keita   • Twitter:   / zoumana_keita_   • TikTok:   / zoumdatascience   • Email me: [email protected] • 🎙️ Support me: https://www.buymeacoffee.com/zoumanakeig • • #artificialintelligence #gpt4 #openai #largelanguagemodels

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