Search Results for "collaborative filtering"

This project provides fast Python implementations of several different popular recommendation algorithms for implicit feedback datasets. All models have multi-threaded training routines, using Cython and OpenMP to fit the models in parallel among all available CPU cores. In addition, the ALS and BPR models both have custom CUDA kernels - enabling fitting on compatible GPU’s. This library also supports using approximate nearest neighbour libraries such as Annoy, NMSLIB and Faiss for speeding...

...The project has evolved from a personal tool to a collaborative open-source effort with beta-phase features including a dashboard, flexible proxy engine, and compatibility with multiple output formats. With extensible plugin support and frequent contributions, Dispatcharr aims to unify and simplify IPTV workflows while staying entirely self-hosted.

...A user's "star" ratings are scraped from their Letterboxd profile and assigned numerical ratings from 1 to 10 (accounting for half stars). Their ratings are then combined with a sample of ratings from the top 4000 most active users on the site to create a collaborative filtering recommender model using singular value decomposition (SVD). All movies in the full dataset that the user has not rated are run through the model for predicted scores and the items with the top predicted scores are returned. Due to constraints in time and computing power, the maximum sample size that a user is allowed to select is 500,000 samples, though there are over five million ratings in the full dataset from the top 4000 Letterboxd users alone.

FloPy is a utility application that simplifies the process of loading, filtering, and saving specific data from various file formats, including ".csv", ".xls", and ".xlsx". Its user-friendly graphical interface (GUI) ensures that anyone can use the application with ease. ### Author ### This project was created by SUVANKAR BANERJEE. You can find more about the author and contribute to the project on GitHub. ### License ### FloPy is released under the MIT License, promoting open and collaborative software development.

Cherche allows the creation of efficient neural search pipelines using retrievers and pre-trained language models as rankers. Cherche's main strength is its ability to build diverse and end-to-end pipelines from lexical matching, semantic matching, and collaborative filtering-based models. Cherche provides modules dedicated to summarization and question answering. These modules are compatible with Hugging Face's pre-trained models and fully integrated into neural search pipelines. Search is fully compatible with the collaborative filtering library Implicit. It is advantageous if you have a history associated with users and you want to retrieve / re-rank documents based on user preferences.

MLPACK is a C++ machine learning library with emphasis on scalability, speed, and ease-of-use. Its aim is to make machine learning possible for novice users by means of a simple, consistent API, while simultaneously exploiting C++ language features to provide maximum performance and flexibility for expert users. * More info + downloads: https://mlpack.org * Git repo: https://github.com/mlpack/mlpack

Awesome Artificial Intelligence, Machine Learning and Deep Learning as we learn it. Study notes and a curated list of awesome resources of such topics. This repo is dedicated to engineers, developers, data scientists and all other professions that take interest in AI, ML, DL and related sciences. To make learning interesting and to create a place to easily find all the necessary material. Please contribute, watch, star, fork and share the repo with others in your community.

The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming"

Cyn.in helps teams to build collaborative knowledge by sharing & discussing digital content within secure & unified application. It combines the capabilities of wikis, social network, blogs, files, microblogs, discussions into secure enterprise platform.

"Filtered communication" is the source code for a website which facilitates collaborative filtering of information on the internet. Users can create "filters", criteria which are defined in English. Activity mode (http://bayleshanks.com/pamv1): aslee