The course provides a comprehensive guide to optimizing retrieval systems in large-scale RAG applications. It covers tokenization, vector quantization, and search optimization techniques to enhance search quality, reduce memory usage, and balance performance in vector search systems.
data-science machine-learning natural-language-processing machinelearning search-algorithm tokenization rag hnsw search-optimization vectorquantization vectorsearch retrieval-augmented-generation rag-systems retrievaloptimization ragsystems embeddingmodels searchoptimization
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Updated
Dec 28, 2024 - Jupyter Notebook