An open source recommender system service written in Go
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Sep 30, 2021 - Go
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An open source recommender system service written in Go
A Curated List of Must-read Papers on Recommender System.
A Python implementation of LightFM, a hybrid recommendation algorithm.
Papers on Computational Advertising
Alink is the Machine Learning algorithm platform based on Flink, developed by the PAI team of Alibaba computing platform.
Accelerated deep learning R&D
Classic papers and resources on recommendation
Deep recommender models using PyTorch.
Fast Python Collaborative Filtering for Implicit Feedback Datasets
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
An index of algorithms for learning causality with data
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
Machine Learning Platform and Recommendation Engine built on Kubernetes
A Deep Learning Recommender System
Neural Collaborative Filtering
Came up in jfkirk/tensorrec#31
It would be nice to have an arg to re-order the batches every epoch while fitting.
shuffle_batches arg to fit() and fit_partial() that shuffles the batch order every epoch if TrueRecurrence the recommender paper with Tensorflow2.0
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
fastFM: A Library for Factorization Machines
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
The awesome and classic papers in recommendation system!!! Good luck to every RecSys-learner!
深度学习入门课、资深课、特色课、学术案例、产业实践案例、深度学习知识百科及面试题库The course, case and knowledge of Deep Learning and AI
A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.
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I am finding a product which can replace Elasticsearch.