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1. 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
2. Diving into Word Embeddings with EDA

   Exploratory data analysis (EDA) is a powerful technique to understand the structure of word embeddings, the basis of large language models. In this article, we'll apply EDA to GloVe word embeddings and find some interesting insights.

   2024-07-12 Tags: word, embeddings, eda, glove, pca, dimensionality reduction, nlp, text, python by klotz
3. Mastering Customer Segmentation with LLM

   Unlock advanced customer segmentation techniques using LLMs, and improve your clustering models with advanced techniques

   2023-09-28 Tags: llm, segmentation, kmeans, k prototype, tsne, pca, sentence, embedding, clustering, exploratory data analysis by klotz
4. How to Solve Analogies with Word2Vec - Towards Data Science

   2020-03-13 Tags: word2vec, word embedding, analogy, tutorial, machine learning, deep learning, pca, visualization by klotz
5. Comparing the performance of non-supervised vs supervised learning methods for NLP text…

   2018-10-19 Tags: nlp, machine learning, tf-idf, classification, k-means, pca, lda by klotz
6. GitHub - lmcinnes/umap: Uniform Manifold Approximation and Projection

   Alternative to t-SNE and PCA

   2018-10-09 Tags: umap, visualization, dimensionality reduction, python, embedding, machine learning, t-sne, pca by klotz

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