GitHub topics: pairwise-distances
JuliaStats/Distances.jl
A Julia package for evaluating distances (metrics) between vectors.
Language: Julia - Size: 342 KB - Last synced at: about 2 months ago - Pushed at: about 2 months ago - Stars: 447 - Forks: 98
abhinavnatarajan/RedClust.jl
Julia package to perform Bayesian clustering of high-dimensional Euclidean data using pairwise dissimilarity information.
Language: Julia - Size: 10.9 MB - Last synced at: 1 day ago - Pushed at: 11 months ago - Stars: 5 - Forks: 0
kunal-mallick/Book_Recommendation
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.
Language: Jupyter Notebook - Size: 115 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0
rajeevvhanhuve/Book-Rental-Recommendation
Machine Learning
Language: Jupyter Notebook - Size: 17.1 MB - Last synced at: about 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 5
RozaAbolghasemi/Group_Recommendation_Syatem_GcPp_clustering
A Jupyter notebook for a project centered around 'Group Recommendation Systems (GRS)' utilizing the 'GcPp' clustering approach.
Language: Jupyter Notebook - Size: 1.16 MB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 5 - Forks: 0
seth-brown/furlong
A zero-dependency Typescript library for computing pairwise distances
Language: TypeScript - Size: 434 KB - Last synced at: 17 days ago - Pushed at: over 2 years ago - Stars: 7 - Forks: 0
saikrishnabudi/Recommendation-System
Data Science - Recommendation Work
Language: Jupyter Notebook - Size: 273 KB - Last synced at: over 1 year ago - Pushed at: over 1 year ago - Stars: 0 - Forks: 0
paul-lindquist/spotify-recommendation-system
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
Language: Jupyter Notebook - Size: 83.6 MB - Last synced at: over 1 year ago - Pushed at: almost 3 years ago - Stars: 0 - Forks: 1
vaitybharati/P35.-Unsupervised-ML---Recommendation-System-Data-Mining-Movies-
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 column names to user ids, Slicing first 5 rows and first 5 columns, Nullifying diagonal values, Most Similar Users, extract the movies which userId 6 & 168 have watched.
Language: Jupyter Notebook - Size: 10.7 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
vaitybharati/Recommendation-Engine
Recommendation-Engine
Language: Jupyter Notebook - Size: 1.95 KB - Last synced at: over 1 year ago - Pushed at: over 4 years ago - Stars: 1 - Forks: 0
vaitybharati/Assignment-10-Recommendation-System-Data-Mining-books-
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 Cosine Similarity between Users on array data, Store the results in a dataframe format, Set the index and column names to user ids, Nullifying diagonal values, Most Similar Users, extract the books which userId 162107 & 276726 have watched, extract the books which userId 276729 & 276726 have watched.
Language: Jupyter Notebook - Size: 12.7 KB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
Pradnya1208/Similar-product-recommendation-system-using-CNN
In this repository, we have implemented the CNN based recommendation system for finding similar products.
Language: Jupyter Notebook - Size: 8.23 MB - Last synced at: about 2 years ago - Pushed at: over 3 years ago - Stars: 1 - Forks: 0
shanuhalli/Assignment-Recommendation-System
Build a recommender system by using cosine simillarties score - books dataset.
Language: Jupyter Notebook - Size: 328 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
oliviaguest/pdist
Calculate mean of pairwise weighted distances between points using great circle metric.
Language: Python - Size: 70.3 KB - Last synced at: 12 months ago - Pushed at: almost 2 years ago - Stars: 11 - Forks: 2
