A WebGL2 fragment shader based raytracer

As part of the UCSanDiego online course "Machine Learning Fundamentals"

This repository contains two implementations of a K-Nearest Neighbors (KNN) classifier for predicting online shopping behavior. The classifiers are implemented in Python and use different approaches for finding the nearest neighbors: Naive Implementation, KDTree Implementation

MultiDimensional Data Structures Project

基于 KD-Tree 实现的近似查询处理（AQP）问题

Code corresponding to M1 - Advanced data structures course, ECI36 2023

This package will reverse geocode i.e., take a latitude and longitude coordinate which will return the country, city name, alternate name(s), population, timezone, and exact coordinates of the city.

A* implementation with open street maps data to compute shortest path on maps with kd-tree and mean of means algorithm.

Прогнозирование эмоциональной окраски отзывов.

Unofficial python wrapper to the nanoflann k-d tree

Fast Near-Duplicate Image Search and Delete using pHash, t-SNE and KDTree.

A simple and fast KD-tree for points in Python for kNN or nearest points. (damm short at just ~60 lines) No libraries needed.

Build content-based image retrieval system using deep learning, applied some large scale similarity search technicals like Kdtree, LSH, Faiss.

Toolbox for interpolating from an uneven grid

Python implementation of a K-D Tree as pseudo-balanced Tree

Implement a Hastable with n buckets and each bucket should be an implementation of KDTree with 2 dimensions

kd tree spatial index algorighm

The final project for the Geometric Algorithms Course at AGH UST

K dimensional Tree

machine learning algorithms implementation by PYTHON3