kakao/n2
TOROS N2 - lightweight approximate Nearest Neighbor library which runs fast even with large datasets
This library helps you quickly find the most similar data points to a given item within very large datasets. You input a collection of data points (vectors) and then query with a new data point to efficiently get back a list of the closest matches. Data scientists, machine learning engineers, and anyone working with high-dimensional data would use this for tasks like recommendation systems or information retrieval.
580 stars. No commits in the last 6 months.
Use this if you need to perform fast 'nearest neighbor' searches on extensive datasets, prioritizing speed and efficient memory usage.
Not ideal if your dataset is small or if you require perfectly exact nearest neighbor results rather than approximate ones.
Stars
580
Forks
70
Language
Jupyter Notebook
License
Apache-2.0
Category
Last pushed
Jun 27, 2023
Commits (30d)
0
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