🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
-
Updated
Jan 31, 2024 - Rust
🚀 efficient approximate nearest neighbor search algorithm collections library written in Rust 🦀 .
Nearest Neighbor Search with Neighborhood Graph and Tree for High-dimensional Data
TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast even with large datasets
Official code for "DaisyRec 2.0: Benchmarking Recommendation for Rigorous Evaluation" (TPAMI2022) and "Are We Evaluating Rigorously? Benchmarking Recommendation for Reproducible Evaluation and Fair Comparison" (RecSys2020)
Learning to create Machine Learning Algorithms
The first machine learning framework that encourages learning ML concepts instead of memorizing class functions.
Java library for approximate nearest neighbors search using Hierarchical Navigable Small World graphs
Python machine learning applications in image processing, recommender system, matrix completion, netflix problem and algorithm implementations including Co-clustering, Funk SVD, SVD++, Non-negative Matrix Factorization, Koren Neighborhood Model, Koren Integrated Model, Dawid-Skene, Platt-Burges, Expectation Maximization, Factor Analysis, ISTA, F…
Machine Learning Algorithms on NSL-KDD dataset
Interactive K-Nearest Neighbors machine learning algorithm in JavaScript.
Essential NLP & ML, short & fast pure Python code
GloVe word vector embedding experiments (similar to Word2Vec)
Using Tensorflow and a Support Vector Machine to Create an Image Classifications Engine
Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN
Today, using machine learning algorithms is as easy as "import knn from ..." but it doesn't really help if you want to learn how the algorithms work
A general purpose text classifier
Rcpp bindings for the approximate nearest neighbors library hnswlib
Time Series Forecasting of Walmart Sales Data using Deep Learning and Machine Learning
The original lightweight introduction to machine learning in Rubix ML using the famous Iris dataset and the K Nearest Neighbors classifier.
Add a description, image, and links to the k-nearest-neighbors topic page so that developers can more easily learn about it.
To associate your repository with the k-nearest-neighbors topic, visit your repo's landing page and select "manage topics."