Python K-nearest-neighbours Resources

Memorizing Transformers - Pytorch Implementation of Memorizing Transformers (ICLR 2022), attention net augmented with indexing and retrieval of memori

Rethinking Semantic Segmentation: A Prototype View Rethinking Semantic Segmentation: A Prototype View, Tianfei Zhou, Wenguan Wang, Ender Konukoglu and

Machine Learning With Python Get started with Machine Learning with Python An engaging introduction to Machine Learning with Python TL;DR Download all

Billion-Scale ANN http://big-ann-benchmarks.com/ Install The only prerequisite is Python (tested with 3.6) and Docker. Works with newer versions of Py

Benchmarking nearest neighbors Doing fast searching of nearest neighbors in high dimensional spaces is an increasingly important problem, but so far t

GPU implementation of kNN and SNN GPU implementation of $k$-Nearest Neighbors and Shared-Nearest Neighbors Supported by numba cuda and faiss library E

Neighbourhood Retrieval with Distance Correlation Assign Pseudo class labels to datapoints in the latent space. NNDC is a slim wrapper around FAISS. N

TBSG: Tree-based Search Graph for Approximate Nearest Neighbor Search. TBSG is a graph-based algorithm for ANNS based on Cover Tree, which is also an

Model-Based-Recommender-Engine I created a book Recommender System using Sci-kit learn's N-neighbours algorithm for my model and the streamlit library

Python Machine Learning Jupyter Notebooks (ML website) Dr. Tirthajyoti Sarkar, Fremont, California (Please feel free to connect on LinkedIn here) Also

K Nearest Neighbors (KNN) algorithm In this Machine Learning world, there are various algorithms designed for classification problems such as Logistic

Approximate Nearest Neighbor Negative Contrastive Learning for Dense Text Retrieval This repo provides personal implementation of paper Approximate Ne

Point Cloud Utils (pcu) - A Python library for common tasks on 3D point clouds Point Cloud Utils (pcu) is a utility library providing the following fu

Duplicate Image Detection Getting Started Install dependencies pip install -r requirements.txt Run service python main.py Testing Test with pytest How

KNN With Spark Implementation of KNN using PySpark. The KNN was used on two separate datasets (https://archive.ics.uci.edu/ml/datasets/iris and https:

Rethinking Nearest Neighbors for Visual Classification arXiv Environment settings Check out scripts/env_setup.sh Setup data Download the following fin

kNN_From_Scratch I implemented the k nearest neighbors (kNN) classification algorithm on python. This algorithm is used to predict the classes of new

SPTAG: A library for fast approximate nearest neighbor search SPTAG SPTAG (Space Partition Tree And Graph) is a library for large scale vector approxi

Pytorch KNN CUDA 2019/11/02 This repository will no longer be maintained as pytorch supports sort() and kthvalue on tensors. git clone https://github.

PyNNDescent PyNNDescent is a Python nearest neighbor descent for approximate nearest neighbors. It provides a python implementation of Nearest Neighbo

Approximate Nearest Neighbor Search for Sparse Data in Python! This library is well suited to finding nearest neighbors in sparse, high dimensional spaces (like text documents).

Optimal space decomposition based-product quantization for approximate nearest neighbor search Abstract Product quantization(PQ) is an effective neare

NLN: Nearest-Latent-Neighbours A repository containing the implementation of the paper entitled Improving Novelty Detection using the Reconstructions

kNN-vs-RFR My project contrasts K-Nearest Neighbors and Random Forrest Regressors on Real World data In many areas, rental bikes have been launched to

TSP-Nearest-Insertion A raw implementation of the nearest insertion algorithm to resolve TSP problems in a TXT format. Instructions Load a txt file wi

A framework for building (and incrementally growing) graph-based data structures used in hierarchical or DAG-structured clustering and nearest neighbor search

Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

structshot Code and data for paper "Simple and Effective Few-Shot Named Entity Recognition with Structured Nearest Neighbor Learning", Yi Yang and Arz

Fast k-NN graph construction for slow metrics

emoji-math computes the given python expression and returns either the value or the nearest 5 emojis as measured by cosine similarity.

Segmentation and Identification of Vertebrae in CT Scans using CNN, k-means Clustering and k-NN If you use this code for your research, please cite ou

OpenHands OpenHands is a gesture recognition system powered by OpenPose, k-nearest neighbours, and local outlier factor. Currently the system can iden

Efficient implementations of Product Quantization and its variants using Pytorch and CUDA

Comprehensive and Rigorous Framework for Reproducible Recommender Systems Evaluation

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

SeaLion is designed to teach today's aspiring ml-engineers the popular machine learning concepts of today in a way that gives both intuition and ways of application. We do this through concise algorithms that do the job in the least jargon possible and examples to guide you through every step of the way.

a fast, flexible machine learning library Home | Documentation | Doxygen | Community | Help | IRC Chat Download: current stable version (3.4.2) mlpack

Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer

Annoy Annoy (Approximate Nearest Neighbors Oh Yeah) is a C++ library with Python bindings to search for points in space that are close to a given quer

README: python-timbl Authors: Sander Canisius, Maarten van Gompel Contact: [email protected] Web site: https://github.com/proycon/python-timbl/ pytho