Announcing a new Coursera course: Retrieval Augmented Generation (RAG) You'll learn to build high performance, production-ready RAG systems in this hands-on, in-depth course created by DeepLearning.AI and taught by Zain Hasan, experienced AI and ML engineer, researcher, and educator. RAG is a critical component today of many LLM-based applications in customer support, internal company Q&A systems, even many of the leading chatbots that use web search to answer your questions. This course teaches
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Announcing a new Coursera course: Retrieval Augmented Generation (…
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New short course on advanced retrieval for RAG (retrieval augmented generation)! RAG fetches relevant documents to give context to an LLM. In Advanced Retrieval for AI with Chroma, taught by Chroma founder Anton Troynikov, you’ll learn: (i) Query expansion using an LLM to rewrite and improve a query, by either generating either additional relevant queries or a hypothetical answer to the query. (ii) Reranking using a cross-encoder - a model trained to measure similarity between two inputs present
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New short course "Multimodal RAG: Chat with Videos," developed with Intel and taught by Vasudev Lal! In this course, you’ll work with LLaVA (Large Language and Vision Assistant), a Large Vision Language Model (LVLM) that can process both images and text. For example, given an image of a person doing a handstand on a skateboard at the beach, LLaVA doesn't just caption the scene, it’s able to predict possible outcomes, like the person losing balance or falling off. By understanding not just what's
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Build better RAG by letting a team of agents extract and connect your reference materials into a knowledge graph. Our new short course, “Agentic Knowledge Graph Construction,” taught by Neo4j Innovation Lead Andreas Kollegger, shows you how. Knowledge graphs are an important way to store information accurately but they are a lot of work to build manually. In this course you’ll learn how to build a team of agents that turn data– in this case product reviews and invoices from suppliers–into struct
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Come learn about Vector databases! They are a key part of many LLM applications that need search or data retrieval, for example with Retrieval Augmented Generation (RAG). Learn how they work how to use them in our new short course taught by Weaviate’s Sebastian Witalec: https://www.deeplearning.ai/short-courses/vector-databases-embeddings-applications | Andrew Ng
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Learn Retrieval Augmented Generation (RAG) with Coursera course | Andrew Ng posted on the topic | LinkedIn
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Learn to optimize RAG for cost and performance in our new short course, Prompt Compression and Query Optimization, created with MongoDB and taught by Richmond Alake. This course teaches you to combine traditional database capabilities with vector search using MongoDB for RAG. You'll learn these techniques: - Vector search: For semantic matching of user queries - Filtering using metadata: Pre- and post-filtering to narrow search results - Projections: Selecting only necessary fields to minimize d
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