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Introduction to RAG
Short video describing the module's objectives and tasks
Build a complete Retrieval-Augmented Generation pipeline that connects semantic retrieval with LLM generation. Explore contrastive triplet datasets, bi-encoder fine-tuning, embedding normalization, vector stores, efficient top-k search, and knowledge-grounded inference.
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Large Language Models: Build, Fine-Tune and Deploy LLMs
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Large Language Models: Build, Fine-Tune and Deploy LLMs
