SemanticScuttle - klotz.me

klotz: llm embeddings* + natural language processing*

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1. Build Semantic Search with LLM Embeddings

   Learn how to build a simple semantic search engine using sentence embeddings and nearest neighbors, focusing on the limitations of keyword-based search and leveraging large language models for semantic understanding.

   2026-03-05 Tags: semantic search, llm embeddings, sentence transformers, nearest neighbors, natural language processing, machine learning, search engine, text embeddings, cosine similarity, retrieval augmented generation by klotz
2. Document Clustering with LLM Embeddings in scikit-learn

   This tutorial demonstrates how to perform document clustering using LLM embeddings with scikit-learn. It covers generating embeddings with Sentence Transformers, reducing dimensionality with PCA, and applying KMeans clustering to group similar documents.

   2026-02-11 Tags: document clustering, llm embeddings, sentence transformers, scikit-learn, pca, kmeans, dimensionality reduction, natural language processing, nlp by klotz

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