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Vector Search and RAG Tutorial – Using LLMs with Your Data

4.6 (356) · $ 19.00 · In stock

You can use Vector Search and embeddings to easily combine your data with large language models like GPT-4. I just published a course on the channel that will teach you how to implement Vector Search on three different projects. First, you will learn about the concepts and then
You can use Vector Search and embeddings to easily combine your data with large language models like GPT-4. I just published a course on the channel that will teach you how to implement Vector Search on three different projects. First, you will learn about the concepts and then I'll guide you through developing three projects. In the first project we build a semantic search feature to find movies using natural language queries. For this we use Python, machine learning

Retrieval Augmented Generation (RAG)

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Gartner RAG Tips for Grounding LLMs with Relevant Internal Data

Improve your RAG application response quality with real-time structured data

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