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Name: Sony
Type: User
Company: Free
Bio: I am the Fobia, a passionate user who finds joy in collecting and sharing useful resources.
Location: Somewhere on the Earth!
Name: Sony
Type: User
Company: Free
Bio: I am the Fobia, a passionate user who finds joy in collecting and sharing useful resources.
Location: Somewhere on the Earth!
[TKDE 2021] Source code and datasets for the paper "Personalizing Graph Neural Networks with Attention Mechanism for Session-based Recommendation"
The latest research progress of Contrastive Learning(CL), Data Augmentation(DA) and Self-Supervised Learning(SSL) in Recommender Systems
The most cited deep learning papers
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
Survey: A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.
Paper List for Recommend-system PreTrained Models
A curated list of awesome Recommender System (Books, Conferences, Researchers, Papers, Github Repositories, Useful Sites, Youtube Videos)
Recommender System Papers
This is the homepage of a new book entitled "Mathmatical Foundations of Reinforcement Learning."
This repository contains data on Coronavirus Disease 2019 (COVID-19) in New York City (NYC), from the NYC Department of Health and Mental Hygiene.
DS4C: Data Science for COVID-19 in South Korea
Data-Scientist-Books (Machine Learning, Deep Learning, Natural Language Processing, Computer Vision, Long Short Term Memory, Generative Adversarial Network, Time Series Forecasting, Probability and Statistics, and more.)
A repository to keep track of all the code that I end up writing for my blog posts.
Examples of Data Science projects and Artificial Intelligence use-cases
This repo contains datasets used in trainings.
This repository contains Deep Learning based articles , paper and repositories for Recommender Systems
These are Some useful ebook
An index of recommendation algorithms that are based on Graph Neural Networks.
Introduction to Statistics and Basics of Mathematics for Data Science - The Hacker's Way
The datasets can be used for POI/next-POI recommendation, trajectory recommendation, friends recommendation (link prediction), activity recommendations, group recommendation and community discovery tasks.
A list of awesome papers and resources of recommender system on large language model (LLM).
🧮 A collection of resources to learn mathematics for machine learning
📋 Survey papers summarizing advances in deep learning, NLP, CV, graphs, reinforcement learning, recommendations, graphs, etc.
Recommender Systems Paperlist that I am interested in
A list of data sets for research on recommender systems
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.