| Abstract: | This course explores Multimodal Retrieval-Augmented Generation (RAG) with GPT-4, teaching you to build smarter search and recommendation systems. You'll begin by understanding RAG fundamentals and how combining text and image data creates context-aware AI solutions. A guided development environment setup ensures you're ready to implement and test concepts effectively. You'll then dive into the workings and benefits of multimodal RAG systems. Learn how integrating text and visual embeddings enhances search precision and why multimodal search is a game-changer for modern AI applications. Step-by-step, you'll build a multimodal search system, generate image embeddings, and connect them into a functional workflow to see the power of multimodal AI in action. The course culminates in building a multimodal recommendation system using GPT-4. You'll process datasets, save embeddings to a vector database, and test the system's performance. Finally, you'll integrate an interactive user interface with Streamlit, creating a production-ready AI solution. By the end, you'll be equipped to scale these systems for real-world applications and unlock new opportunities with multimodal AI. To access the supplementary materials, scroll down to the 'Resources' section above the 'Course Outline' and click 'Supplemental Content.' This will either initiate a download or redirect you to GitHub. What you will learn Build multimodal search and recommendation systems using RAG frameworks Integrate text and image embeddings into a unified AI system Set up and manage vector databases for efficient search and retrieval Implement workflows for multimodal RAG, enhancing system performance Create user-friendly UIs for testing and deploying intelligent solutions Optimize multimodal systems for accuracy and real-world scalability Audience This course is ideal for machine learning engineers, AI developers, and technical professionals looking to enhance their expertise in multimodal systems. Prerequisites include a basic understanding of Python programming, machine learning concepts, and familiarity with tools like Hugging Face and vector databases. About the Author Paulo Dichone: Paulo Dichone, a dedicated developer and educator in Android, Java, and Flutter, has empowered over 80,000 students globally with both soft and technical skills through his platform, Build Apps with Paulo. Holding a Computer Science degree and with extensive experience in mobile and web development, Paulo's passion lies in guiding learners to become proficient developers. Beyond his 5 years of online teaching, he cherishes family time, music, and travel, aiming to make impactful developers irrespective of their background. |
|---|
Online-Ressource
Zum Volltext
Bestellen/Vormerken für Benutzer des Klinikums Mannheim
