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1. Introducing sqlite-vec v0.1.0: a vector search SQLite extension that runs everywhere

   Introducing sqlite-vec, a new SQLite extension for vector search written entirely in C. It's a stable release and can be installed in multiple ways. It runs on various platforms, is fast, and supports quantization techniques for efficient storage and search.

   2024-08-04 Tags: sqlite-vec, sqlite, vector search, embeddings, quantization, database, ann, knn, machine learning by klotz
2. 1.6. Nearest Neighbors — scikit-learn 0.24.2 documentation

   >>> from sklearn.neighbors import NearestCentroid
   >>> import numpy as np
   >>> X = np.array( [-1, -1 » , -2, -1 » , -3, -2 » , 1, 1 » , 2, 1 » , 3, 2 » ])
   >>> y = np.array( 1, 1, 1, 2, 2, 2 » )
   >>> clf = NearestCentroid()
   >>> clf.fit(X, y)
   NearestCentroid()
   >>> print(clf.predict( [-0.8, -1 » ]))
   1 »

   2021-09-02 Tags: knn, centroid, machine learning, numpy, python by klotz
3. Midnight Hack 5: Using Machine Learning to categorize Spotify playlists | by Sanat Dutta | Jun, 2021 | Towards Data Science

   2021-06-21 Tags: spotify, knn, random forest, machine learning, tsne, music, classification by klotz
4. python - How can i plot a Kmeans text clustering result with matplotlib? - Stack Overflow

   In your example if you use PCA to initialize your t-SNE you get widely spaced centroids; if you use random initialization you'll get tiny centroids and an uninteresting picture.

   2018-08-14 Tags: knn, cluster, visualization, python, matplotlib, tf-idf, pca by klotz
5. KNN Classification using Scikit-learn (article) - DataCamp

   2018-08-03 Tags: knn, scikit-learn by klotz

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