A Python implementation of LightFM, a hybrid recommendation algorithm.
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Updated
May 21, 2024 - Python
A Python implementation of LightFM, a hybrid recommendation algorithm.
Learning to Rank in TensorFlow
An index of algorithms for learning causality with data
Deep recommender models using PyTorch.
A machine learning tool that ranks strings based on their relevance for malware analysis.
allRank is a framework for training learning-to-rank neural models based on PyTorch.
Python learning to rank (LTR) toolkit
Awesome Search - this is all about the (e-commerce, but not only) search and its awesomeness
Tensorflow implementations of various Learning to Rank (LTR) algorithms.
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.
ICCV 2019 (oral) RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolution. PyTorch implementation
My (slightly modified) Keras implementation of RankNet and PyTorch implementation of LambdaRank.
Code for WWW'19 "Unbiased LambdaMART: An Unbiased Pairwise Learning-to-Rank Algorithm", which is based on LightGBM
Factorization Machines for Recommendation and Ranking Problems with Implicit Feedback Data
A library for preparing, training, and evaluating scalable deep learning hybrid recommender systems using PyTorch.
This demo uses data from TheMovieDB (TMDB) to demonstrate using Ranklib learning to rank models with Elasticsearch.
Must-read Papers for Recommender Systems (RS)
train models in pytorch, Learn to Rank, Collaborative Filter, Heterogeneous Treatment Effect, Uplift Modeling, etc
Code for CVPR 2019 paper "Deep Metric Learning to Rank"
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