Trending repositories for topic recommendation-system
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
RecTools - library to build Recommendation Systems easier and faster than ever before
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in p...
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
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.
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
RecTools - library to build Recommendation Systems easier and faster than ever before
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in p...
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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.
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
RecTools - library to build Recommendation Systems easier and faster than ever before
Paper List of Pre-trained Foundation Recommender Models
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in p...
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.
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
Transforming skincare recommendations: our hybrid system combines KNN, CNN, and EfficientNet B0 for personalized advice. Published in IEEE, with 80% validation accuracy and 87.10% training accuracy.
implement basic and contextual MAB algorithms for recommendation system
Food/Diet Recommendation system using machine learning
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
Transforming skincare recommendations: our hybrid system combines KNN, CNN, and EfficientNet B0 for personalized advice. Published in IEEE, with 80% validation accuracy and 87.10% training accuracy.
implement basic and contextual MAB algorithms for recommendation system
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
RecTools - library to build Recommendation Systems easier and faster than ever before
Paper List of Pre-trained Foundation Recommender Models
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM, xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... （pytorch, tf2.0）
Food/Diet Recommendation system using machine learning
A Comparative Framework for Multimodal Recommender Systems
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in p...
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
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.
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in p...
RecTools - library to build Recommendation Systems easier and faster than ever before
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
Paper List of Pre-trained Foundation Recommender Models
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
Transforming skincare recommendations: our hybrid system combines KNN, CNN, and EfficientNet B0 for personalized advice. Published in IEEE, with 80% validation accuracy and 87.10% training accuracy.
Enhancing Recommendation Systems with Large Language Models (RAG - LangChain - OpenAI)
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
An index of causal inference based recommendation algorithms (TOIS).
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
[WWW2023] PyTorch implementation of "DUET: A Tuning-Free Device-Cloud Collaborative Parameters Generation Framework for Efficient Device Model Generalization".
RecTools - library to build Recommendation Systems easier and faster than ever before
Food/Diet Recommendation system using machine learning
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
推荐系统论文算法实现，包括序列推荐，多任务学习，元学习等。 Recommendation system papers implementations, including sequence recommendation, multi-task learning, meta-learning, etc.
GHRS: Graph-based hybrid recommendation system with application to movie recommendation
The "Medicine Recommendation System" is designed to provide suggestions for alternative or substitute medications based on a search query, with the primary goal of offering viable replacements for the...
implement basic and contextual MAB algorithms for recommendation system
Building a Movie Recommendation System web application using Django framework and Collaborative Filtering technique
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
Enhancing Recommendation Systems with Large Language Models (RAG - LangChain - OpenAI)
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
Fast Python Collaborative Filtering for Implicit Feedback Datasets
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
Paper List of Pre-trained Foundation Recommender Models
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in p...
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
A content-based recommender system that recommends movies similar to the movie the user likes and analyses the sentiments of the reviews given by the user
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
Food/Diet Recommendation system using machine learning
[ECIR'24] Implementation of "Large Language Models are Zero-Shot Rankers for Recommender Systems"
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
A collection of personally developed projects contributing towards the advancement of Artificial General Intelligence(AGI)
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
Food/Diet Recommendation system using machine learning
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
Paper List of Pre-trained Foundation Recommender Models
The "Medicine Recommendation System" is designed to provide suggestions for alternative or substitute medications based on a search query, with the primary goal of offering viable replacements for the...
An Awesome Collection for Sequential Recommendation and Sequence Modeling in Recommend System
Spotify Recommendation System Using Spotify Million Playlist Dataset
推荐系统论文算法实现，包括序列推荐，多任务学习，元学习等。 Recommendation system papers implementations, including sequence recommendation, multi-task learning, meta-learning, etc.
Movie Recommendation System with Complete End-to-End Pipeline, Model Intregration & Web Application Hosted. It will also help you build similar projects.
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.
Movie Recommendation System: Project using R and Machine learning
implement basic and contextual MAB algorithms for recommendation system
[Neurocomputing 2023] Relational Graph Transformer for Knowledge Graph Representation
Furniture Object Detector & Recommender using Detectron2 & VGG16 (IKEA Furniture Recommender)