Best Practices on Recommendation Systems

Learning to Rank in TensorFlow

⭐ Web frameworks for Go, most starred on GitHub

Multi-Task Deep Neural Networks for Natural Language Understanding

A web app for ranking computer science departments according to their research output in selective venues.

🕷️Github 中国和全球用户排名，全球仓库 Star 最多排名(自动日更)。

DeText: A Deep Neural Text Understanding Framework for Ranking and Classification Tasks

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.

Case Recommender: A Flexible and Extensible Python Framework for Recommender Systems

🎶 The ultimate community-driven, and open-source competitive rhythm game.

allRank is a framework for training learning-to-rank neural models based on PyTorch.

multi_task_NLP is a utility toolkit enabling NLP developers to easily train and infer a single model for multiple tasks.

Fast Differentiable Sorting and Ranking

A tensorflow implementation of Learning to Rank Short Text Pairs with Convolutional Deep Neural Networks

⭐Github Ranking⭐ 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

Comparison tools

Learning to Rank in PyTorch

A collection of BM25 algorithm variants

Grade exams fast and accurately using a scanner 🖨 or your phone 🤳.

A Machine Learning and Optimization framework for Objective-C and Swift (MacOS and iOS)

A PHP Bot that assigns time based server groups on TeamSpeak3.

“Chorus” of recommendation models: a PyTorch framework for Top-K recommendation with implicit feedback.

ElasticCTR，即飞桨弹性计算推荐系统，是基于Kubernetes的企业级推荐系统开源解决方案。该方案融合了百度业务场景下持续打磨的高精度CTR模型、飞桨开源框架的大规模分布式训练能力、工业级稀疏参数弹性调度服务，帮助用户在Kubernetes环境中一键完成推荐系统部署，具备高性能、工业级部署、端到端体验的特点，并且作为开源套件，满足二次深度开发的需求。

Inference algorithms for models based on Luce's choice axiom

🧹 Formerly for binary classification with noisy labels. Replaced by cleanlab.

📈 Node.js API to retrieve the top songs, albums, and artists from Billboard's charts

Fork and custom implementation of LineUp Library for Visual Analysis of Multi-Attribute

Search R packages on CRAN

PyTorch and TensorFlow Implementations For A Series Of Deep Learning-Based Recommendation Models (IN PROGRESS)

Visual is a Javascript library for data visualization developed by the Statistical Institute of Catalonia (Idescat). It is based on popular open source solutions. Visual offers a simple interface that encapsulates the complexity of these solutions for the most common chart types.