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
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.
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
🔥🔥🔥 Latest Advances on Large Recommendation Models
🔥🔥🔥 Latest Advances on Large Recommendation Models
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.
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
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
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.
🔥🔥🔥 Latest Advances on Large Recommendation Models
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
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"
Paper List of Pre-trained Foundation Recommender Models
Basic Movie Recommendation Web Application using user-item collaborative filtering.
RecTools - library to build Recommendation Systems easier and faster than ever before
😎 A curated list of awesome practical Metric Learning and its applications
🔥🔥🔥 Latest Advances on Large Recommendation Models
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
Food/Diet Recommendation system using machine learning
[ECIR'24] Implementation of "Large Language Models are Zero-Shot Rankers for Recommender Systems"
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.
Paper List of Pre-trained Foundation Recommender Models
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
Basic Movie Recommendation Web Application using user-item collaborative filtering.
RecTools - library to build Recommendation Systems easier and faster than ever before
HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training
😎 A curated list of awesome practical Metric Learning and its applications
Fast Python Collaborative Filtering for Implicit Feedback Datasets
🔥🔥🔥 Latest Advances on Large Recommendation Models
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.
🔥🔥🔥 Latest Advances on Large Recommendation Models
[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.
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
An index of recommendation algorithms that are based on Graph Neural Networks. (TORS)
Paper List of Pre-trained Foundation Recommender Models
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"
[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.
Contains Solutions and Notes for the Machine Learning Specialization By Stanford University and Deeplearning.ai - Coursera (2022) by Prof. Andrew NG
Food/Diet Recommendation system using machine learning
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"
[WSDM 2024 Oral] This is our Pytorch implementation for the paper: "Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation".
A curated list of awesome machine learning libraries for marketing, including media mix models, multi touch attribution, causal inference and more
RecTools - library to build Recommendation Systems easier and faster than ever before
[ECIR'24] Implementation of "Large Language Models are Zero-Shot Rankers for Recommender Systems"
A Lighting Pytorch Framework for Recommendation Models, Easy-to-use and Easy-to-extend.
Paper List of Pre-trained Foundation Recommender Models
OpenVINO™ is an open-source toolkit for optimizing and deploying AI inference
整理自然语言处理、推荐系统、搜索引擎等AI领域的入门笔记，论文学习笔记和面试资料（关于NLP那些你不知道的事、关于推荐系统那些你不知道的事、NLP百面百搭、推荐系统百面百搭、搜索引擎百面百搭）
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.
A step-by-step tutorial on developing a practical recommendation system (retrieval and ranking) using TensorFlow Recommenders and Keras.
Basic Movie Recommendation Web Application using user-item collaborative filtering.
[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"
🔥🔥🔥 Latest Advances on Large Recommendation Models
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.
Food/Diet Recommendation system using machine learning
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
[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".
Food/Diet Recommendation system using machine learning
[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"
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
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.
A collection of personally developed projects contributing towards the advancement of Artificial General Intelligence(AGI)
Spotify Recommendation System Using Spotify Million Playlist Dataset
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
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...
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.
An Awesome Collection for Sequential Recommendation and Sequence Modeling in Recommend System
implement basic and contextual MAB algorithms for recommendation system
Movie Recommendation System: Project using R and Machine learning