Complete Java Approach
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Updated
Apr 16, 2016 - Java
Complete Java Approach
Cluster the documents using K-Means clustering Term Frequency - Inverse Document Frequency
This is a java application to find the nearest neighboring document using cosine similarity and euclidean distance
A collection of interesting, memorable, and well... mundane projects developed for and during my bachellor's and master's degree at PUPR(San Juan, PR) and JHU(Baltimore, MD), respectively.
Compute Euclidean and spherical distances. VERY FAST. TINY.
Classic k-means using euclidean distance in C++
MATLAB code for solving the Euclidean Distance Matrix completion problem.
A prototype of a recommender system based on Euclidean Similarity/Pearson Similarity Coefficient
Non-Negative Matrix Factorization for Gene Expression Clustering
Expiremental Speech Recognition System using VHDL & MATLAB.
Data Science Projects
Machine Learning
Euclidiana is a web application that determines different characteristics by means of the Euclidean and Naive Bayes distance algorithm.
A flexible function in TensorFlow, to calculate the Euclidean distance between all row vectors in a tensor, the output is a 2D numpy array.
Image search engine using Angular and Python.
Personalized book recommendation system for a user.Similar to Goodreads.
Finding Covariance Matrix, Correlation Coefficient, Euclidean and Mahalanobis Distance
This repository contains a simple recommendation system
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