Awesome GitHub RepositoriesContent-Based Filtering

Recommenders is a recommendation system framework designed for building, benchmarking, and deploying collaborative and content-based filtering models. It provides a machine learning model pipeline that standardizes the process of moving recommendation data from raw ingestion through training and evaluation. The project functions as a model benchmarking toolkit, utilizing standardized ranking and error metrics to compare the accuracy of different algorithms. It also serves as a hyperparameter tuning tool, allowing for the optimization of model behavior and performance via external configuratio

This project is a recommendation system framework designed for building, evaluating, and operationalizing personalized item suggestion engines. It provides a comprehensive toolkit for implementing collaborative filtering and content-based algorithms, supported by an end-to-end machine learning pipeline for preparing datasets and deploying predictive models. The framework distinguishes itself through the integration of knowledge graphs to provide richer context for recommendations and the use of industry-specific patterns to accelerate system deployment. It also includes a specialized model ev

NewsBlur is an RSS feed aggregator and social news reader that collects and organizes stories from feeds, newsletters, and websites into a single interface. It functions as a feed synchronization service that maintains read states and subscription data across multiple devices and third-party applications. The platform distinguishes itself with AI-powered content summarization to generate briefings and answer questions about articles, alongside a system for training content classifiers. These classifiers learn user preferences for authors and tags to automatically highlight preferred topics or