From the course: Defending and Deploying AI by Pearson
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Vector databases
From the course: Defending and Deploying AI by Pearson
Vector databases
So what are vector databases? I mentioned that a lot throughout the course, but I haven't defined them and we haven't looked at them in detail. At their core, vector databases are specialized databases that are designed to store, manage, and query high-dimensional vectors. In other words, vector embeddings. As we learned, these vector embeddings are the numerical representation of our data, whether it's text, images, audio. Unlike traditional relational database, these databases that are optimized for structured data and exact matches. So we have been talking about vector databases for quite some time in this course, but haven't actually going over in detail what are vector databases. At their core, vector databases are specialized databases that are designed to store, manage, and query high-dimensional vector embeddings. So as we learn, these vectors are the numerical representation, or the embeddings, of our data, whether it's text, images, or audio. Unlike traditional relational…
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Learning objectives1m 30s
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The essentials of RAG7m 21s
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Exploring the GitHub repositories and additional resources3m 40s
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Embeddings and embedding models18m 5s
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Indexing techniques13m 20s
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Vector databases6m 32s
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Chunking strategies9m 47s
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RAG vs. fine-tuning14m 2s
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RAG, RAG Fusion, and RAPTOR11m 51s
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Running open-weight models with Ollama17m
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Exploring Open WebUI and other Ollama plugins12m 47s
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Introduction to AI agents and agentic implementations6m 54s
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Introduction to agentic RAG6m 6s
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Introducing the Model Context Protocol (MCP)14m 19s
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Introducing A2A and AGNTCY20m 57s
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