A Python implementation of LightFM, a hybrid recommendation algorithm.

An index of algorithms for learning causality with data

Deep recommender models using PyTorch.

Learning to Rank in TensorFlow

Awesome Search - this is all about the (e-commerce, but not only) search and its awesomeness

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

A machine learning tool that ranks strings based on their relevance for malware analysis.

Learning to Rank in PyTorch

Python learning to rank (LTR) toolkit

ICCV 2019 (oral) RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution. PyTorch implementation

利用lightgbm做(learning to rank)排序学习，包括数据处理、模型训练、模型决策可视化、模型可解释性以及预测等。Use LightGBM to learn ranking, including data processing, model training, model decision visualization, model interpretability and prediction, etc.

My (slightly modified) Keras implementation of RankNet and PyTorch implementation of LambdaRank.

Tensorflow implementations of various Learning to Rank (LTR) algorithms.

Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM

The codebase for the book "AI-Powered Search" (Manning Publications, 2024)

train models in pytorch, Learn to Rank, Collaborative Filter, Heterogeneous Treatment Effect, Uplift Modeling, etc

Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data

Must-read Papers for Recommender Systems (RS)

The repository for 'Uncertainty-aware blind image quality assessment in the laboratory and wild' and 'Learning to blindly assess image quality in the laboratory and wild'

A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.