Search Results for "collaborative filtering"
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Showing 23 open source projects for "collaborative filtering"
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Implicit
Fast Python collaborative filtering for implicit feedback datasets
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... -
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Dispatcharr
Your Ultimate IPTV & Stream Management Companion
...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. -
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Melos
A tool for managing Dart projects with multiple packages
Melos is a command-line tool designed to manage Dart and Flutter monorepositories by simplifying workflows across multiple interconnected packages. It allows developers to organize large codebases into smaller, independently versioned modules while maintaining a unified development environment. The tool automates common tasks such as dependency linking, versioning, changelog generation, and publishing, reducing manual overhead in multi-package projects. melos integrates closely with Git and... -
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eLabFTW
Open source electronic lab notebook for research labs
eLabFTW is a modern, open-source electronic laboratory notebook (ELN) that helps research teams store, organize, and manage experimental records and laboratory data from a central web interface. Designed for scientific environments, the software provides a secure, browser-accessible platform where users can log protocols, results, and observations in structured records that replace traditional paper notebooks. Beyond simple experiment journaling, eLabFTW includes an inventory database for... -
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Gorse Recommender System Engine
An open source recommender system service written in Go
An open-source recommender system service written in Go. Recommend items from Popular, latest, user-based, item-based and collaborative filtering. Search the best recommendation model automatically in the background. Support horizontal scaling in the recommendation stage after single node training. Support Redis, MySQL, Postgres, MongoDB, and ClickHouse as its storage backend. Expose RESTful APIs for data CRUD and recommendation requests. Analyze online recommendation performance from recently inserted feedback. ... -
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Linkwarden
Self-hosted collaborative bookmark manager
Linkwarden is a self-hosted, open-source bookmark manager built to help individuals and teams collect, organize, and preserve important web content in a way that stays useful long after the original pages change or disappear. Instead of saving only a URL, it captures durable archived formats so your saved knowledge remains accessible even when link rot happens. The experience is designed to feel like a modern “read-it-later” tool, with a reader view that makes long articles easier to consume... -
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Cherche
Neural Search
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. -
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Letterboxd Recommendations
Scraping publicly-accessible Letterboxd data for movie recommendations
...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. -
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FloPy
A python application to extract rows/columns from .csv and .xls files.
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. -
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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
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Awesome AI-ML-DL
Awesome Artificial Intelligence, Machine Learning and Deep Learning
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. -
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Book Recomendation Ssystem
Design By Muhammad Naveed , Contact No/Wahstapp. +923024712782
Project Domain / Category Web Based Abstract/Introduction In this project, we are going to develop an intelligent web-based book store which helps the users (book readers) to not only search the books from the database but also allows the users to see the book recommendations based on their predicted interest. For this purpose, we will include a book recommender module which is based on collaborative filtering. Background of Collaborative Filtering: In e-commerce systems, the recommendation systems are widely used to recommend products to the end users that are most appropriate based on their interest prediction. Such e-commerce systems, the features of collaborative filtering are used to produce efficient and effective recommendations. ... -
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Deep-Learning-for-Recommendation-Systems
This repository contains Deep Learning based articles
Deep-Learning-for-Recommendation-Systems is a curated repository that aggregates research papers, articles, and code related to deep learning methods for recommender systems. The project organizes influential academic work covering topics such as collaborative filtering, neural recommendation models, and deep feature learning. It includes references to papers describing architectures like collaborative deep learning, neural autoregressive models, and convolutional approaches to recommendation. The repository also provides links to implementations and external code repositories that demonstrate how these algorithms can be applied in real systems. ... -
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Oryx
Lambda architecture on Apache Spark, Apache Kafka for real-time
Oryx 2 is a realization of the lambda architecture built on Apache Spark and Apache Kafka, but with specialization for real-time large-scale machine learning. It is a framework for building applications but also includes packaged, end-to-end applications for collaborative filtering, classification, regression and clustering. The application is written in Java, using Apache Spark, Hadoop, Tomcat, Kafka, Zookeeper and more. Configuration uses a single Typesafe Config config file, wherein applications configure an entire deployment of the system. This includes implementations of key interface classes which implement the batch, speed, and serving logic. ... -
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Docmenta
Single Source Publishing Web-Application
Docmenta is a Java web-application for single source publishing and help authoring. The application allows collaborative creation of documentation, e-books and online-help. Supported output formats are PDF, HTML, WebHelp, EPUB (eBook) and DocBook. For more information, visit: http://www.docmenta.org -
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Chronological Cohesive Units
The experimental source code for the paper
The experimental source code for the paper, "A Novel Recommendation Approach Based on Chronological Cohesive Units in Content Consuming" -
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ReSPARQL - RecSPARQL
SPARQL extension for recommendations
...ReSPARQL is an extension of SPARQL that fills the gap between this two paradigms and enables a generic and flexible approach for recommendations over arbitrary RDF-graphs. It supports content-based, collaborative filtering and hybrid recommendations and allows both paradigms to gain benefit from each other. -
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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.
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"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
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Vogoo PHP LIB is a powerful collaborative filtering engine that allows Webmasters to easily add high personalisation features to their Web Sites.
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A collaborative filtering engine developed in PHP. Users submit ratings for different weblogs around the net, and using that information, we can suggest new sites to users with the same likes/dislikes.
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This is a recommendation system built in ruby which is able to generate recommendations for user inputted data (a text file and a ratings matrix). It works on a hybrid model of collaborative filtering and content based filtering.
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