A movie recommendation engine

C++ 3D Vector class and utilities for common vector operations such as euclidean distance, multiplication of vectors, dot, cross, vector-plane intersect, triangle distance, to/from cartesan & spherical coordinates and more.

Get distance between two coordinates using euclidean distance formula

agglomerative hierarchical clustering for Node.js

A K Nearest Neighbors classifier developed from scratch for self-learning purposes. Accuracy is off the charts, since we have full control on the algorithm.

Implementation of K-Nearest Neighbors algorithm rebuilt from scratch using Python. Comparison to the Sci-Kit Learn implementation included.

Classification of IRIS Dataset using various distance metrics.

An example of a minimum distance classificator doing a comparison between using Mahalanobis distance and Euclidean distance.

Predict if teams will take an Offensive (OFF) or Defensive (DEF) player in the 1st round of the 2021 NFL Draft

Forecasting COVID-19 Cases

This course teaches you how to calculate distance metrics, form and identify clusters in a dataset, implement k-means clustering from scratch and analyze clustering performance by calculating the silhouette score

This project is about real-time 2D object recognition. The goal is to have the computer identify a specified set of objects placed on a white surface in a translation, scale, and rotation invariant manner from a camera looking straight down. The computer should be able to recognize single objects placed in the image and identify the objects.

Encoding celebrity dataset with LBP and SIFT and finding matches of given dataset. Option for finding your celebrity lookalike.

Raku package for the computation of various distance functions.

Simple statistical functions that are useful for exploratory spatial data analysis (ESDA) on-the-fly in JavaScript

Library for finding Nearest Neighbor or to find if two points on Earth have a Direct Line of Sight.

Content: Machine Learning, KNN concept, Euclidean distance, Data preprocessing, Scaling the data, Performing train-test split, Applying KNeighbors Classifier, Predicting Y_pred based on X_test, Evaluation using Confusion Matrix, Accuracy score, Recall value & Precision, Underfitting & Overfitting, Measures to overcome Underfitting & Overfitting

This Lua module calculates the "infinite distance" between two sprites and detects the collision between them. Integration of the following specific distance cases: Manhattan distance (K distance with k = 1), Euclidean distance (K distance with k = 2), K distance (with k > 2). Integration of scale factors a and b for sprites.