There are 19 repositories under ranking topic.
Best Practices on Recommendation Systems
:star:Github Ranking:star: Github stars and forks ranking list. Github Top100 stars list of different languages. Automatically update daily. | Github仓库排名,每日自动更新
:star: Web frameworks for Go, most starred on GitHub
Learning to Rank in TensorFlow
A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.
🕷️Github China/Global User Ranking, Global Warehouse Star Ranking (Github Action is automatically updated daily).
Awesome Search - this is all about the (e-commerce, but not only) search and its awesomeness
A Collection of BM25 Algorithms in Python
Fast, differentiable sorting and ranking in PyTorch
Educational material to learn about Goggles and how to create your own.
Fast Differentiable Sorting and Ranking
ORMs for Go, most starred on GitHub.
Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems
专注于解决推荐领域与搜索领域的两个核心问题:排序预测(Ranking)和评分预测(Rating). 为相关领域的研发人员提供完整的通用设计与参考实现. 涵盖了70多种排序预测与评分预测算法,是最快最全的Java推荐与搜索引擎.
multi_task_NLP is a utility toolkit enabling NLP developers to easily train and infer a single model for multiple tasks.
Deep Recommenders
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.
PyTorch Implementations For A Series Of Deep Learning-Based Recommendation Models
A general purpose recommender metrics library for fair evaluation.
Ultra-lite & Super-fast re-ranking for your search & retrieval pipelines. Based on SoTA models like cross-encoders and more. Created by Prithivi Da, open for PRs & Collaborations.
Multiplayer Rating System. No Friction.
SEO: Python script + shell script and cronjob to check ranks on a daily basis
A tensorflow implementation of Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks
A reference implementation of a list ordering system like JIRA's Lexorank algorithm
IResearch is a cross-platform, high-performance search analytics library written entirely in C++ with the focus on a pluggability of different ranking/similarity models