236 Open source projects that are alternatives of or similar to Causal_Reading_Group

Tf-Rec is a python💻 package for building⚒ Recommender Systems. It is built on top of Keras and Tensorflow 2 to utilize GPU Acceleration during training.

A developing recommender system in tensorflow2. Algorithm: UserCF, ItemCF, LFM, SLIM, GMF, MLP, NeuMF, FM, DeepFM, MKR, RippleNet, KGCN and so on.

Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)

Deep recommender models using PyTorch.

Mengting Wan, Julian McAuley, "Item Recommendation on Monotonic Behavior Chains", in Proc. of 2018 ACM Conference on Recommender Systems (RecSys'18), Vancouver, Canada, Oct. 2018.

This repository contains Deep Learning based articles , paper and repositories for Recommender Systems

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Recommender system and evaluation framework for top-n recommendations tasks that respects polarity of feedbacks. Fast, flexible and easy to use. Written in python, boosted by scientific python stack.

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Source code of CHAMELEON - A Deep Learning Meta-Architecture for News Recommender Systems

🛍️RetailBox - eCommerce Recommender System using Machine Learning

Basic Movie Recommendation Web Application using user-item collaborative filtering.

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Recommendation based on sequence

Reinforced Negative Sampling over Knowledge Graph for Recommendation, WWW2020

CRSLab is an open-source toolkit for building Conversational Recommender System (CRS).

MixGCF: An Improved Training Method for Graph Neural Network-based Recommender Systems, KDD2021

1st Solution for 2019-CIKM-Analyticup, Efficient and Novel Item Retrieval for Large-scale Online Shopping Recommendation

PyTorch implementations of Top-N recommendation, collaborative filtering recommenders.

📝 SZU Undergraduate Thesis -- Recommender System

Factorization Machine, Deep Learning, Recommender System

CoFactor: Regularizing Matrix Factorization with Item Co-occurrence

The goal of this survey is two-fold: (i) to present recent advances on adversarial machine learning (AML) for the security of RS (i.e., attacking and defense recommendation models), (ii) to show another successful application of AML in generative adversarial networks (GANs) for generative applications, thanks to their ability for learning (high-…

Sentiment analysis on Amazon Review Dataset available at http://snap.stanford.edu/data/web-Amazon.html

Summary of social recommendation papers and codes

R package for automation of machine learning, forecasting, feature engineering, model evaluation, model interpretation, data generation, and recommenders.

A Python package for causal inference using Synthetic Controls

A recommender system for discovering GitHub repos, built with Apache Spark

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

RiVal recommender system evaluation toolkit

This is our implementation of EATNN: Efficient Adaptive Transfer Neural Network (SIGIR 2019)

跨平台/多语言的 相似向量/相似词/相似句 高性能检索引擎。功能强大，使用方便。欢迎star & fork。Build together! Power another !

This is our implementation of NARRE:Neural Attentional Regression with Review-level Explanations

Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR prediction, CVR prediction), Post Ranking, Transfer, Reinforcement Learning, Self-supervised Learning and so on.

recommender system tutorial with Python

Our implementation of the paper "Embedding-based News Recommendation for Millions of Users"

tf-recsys contains collaborative filtering (CF) model based on famous SVD and SVD++ algorithm. Both of them are implemented by tensorflow in order to utilize GPU acceleration.

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。

🎓 GSU MPA/MPP course on program evaluation and causal inference

Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation

[ WSDM '19 ] Sequential Variational Autoencoders for Collaborative Filtering

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NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.

Towards A Standardized Tag Recommender Benchmarking Framework

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🍃 Recommender System in JavaScript for the MovieLens Database

A system that will help in a personalized recommendation of courses for an upcoming semester based on the performance of previous semesters.

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

This is our implementation of ENMF: Efficient Neural Matrix Factorization (TOIS. 38, 2020). This also provides a fair evaluation of existing state-of-the-art recommendation models.

Building recommender systems in Julia

Deep reinforcement learning for recommendation system

🎯 📕 Targeted Learning in R: A Causal Data Science Handbook

Neural Collaborative Filtering

Nonparametric estimators of the average treatment effect with doubly-robust confidence intervals and hypothesis tests

Exposure Matrix Factorization: modeling user exposure in recommendation

Set of notebooks analysing and discussing the ideas presented at Coursera's Recommender Systems course

Code for our paper, Neural Network Attributions: A Causal Perspective (ICML 2019).

Built on data from Pluralsight's course API fetched results. Works with model trained with K-means unsupervised clustering algorithm.

Joint Geographical and Temporal Modeling based on Matrix Factorization for Point-of-Interest Recommendation - ECIR 2020

Representation Learning and Pairwise Ranking for Implicit Feedback in Top-N Item Recommendation