A Julia package for evaluating distances (metrics) between vectors.

Calculate mean of pairwise weighted distances between points using great circle metric.

A zero-dependency Typescript library for computing pairwise distances

A Jupyter notebook for a project centered around 'Group Recommendation Systems (GRS)' utilizing the 'GcPp' clustering approach.

This repository contains introductory notebooks for recommendation system.

In this repository, we have implemented the CNN based recommendation system for finding similar products.

Julia package to perform Bayesian clustering of high-dimensional Euclidean data using pairwise dissimilarity information.

Unsupervised-ML-Recommendation-System-Data-Mining-Movies. Recommend movies based on the ratings: Sort by User IDs, number of unique users in the dataset, number of unique movies in the dataset, Impute those NaNs with 0 values, Calculating Cosine Similarity between Users on array data, Store the results in a dataframe format, Set the index and co…

Recommendation-Engine

Assignment-10-Recommendation-System-Data-Mining-books. Recommend a best book based on the ratings: Sort by User IDs, number of unique users in the dataset, number of unique books in the dataset, converting long data into wide data using pivot table, replacing the index values by unique user Ids, Impute those NaNs with 0 values, Calculating Cosin…

We are proud to introduce our new book recommendation system, book.io. This system uses the user-to-user collaborative filtering model to recommend books to users based on their preferences and ratings.

Build a recommender system by using cosine simillarties score - books dataset.

Recommend a best book based on the ratings: Sort by User IDs number of unique users in the dataset number of unique books in the dataset converting long data into wide data using pivot table Replacing the index values by unique user Ids Impute those NaNs with 0 values Calculating Cosine Similarity between Users on array data Store the results in…

Machine Learning

Built a content-based recommendation/recommender system specific to electronic music on Spotify using K-Nearest Neighbors (KNN), cosine similarity and sigmoid function kernel to generate similarity and distance-based recommendations. Video of the project presentation: https://lnkd.in/gq5w-4Wm

Data Science - Recommendation Work