[Pytorch] Generative retrieval model using semantic IDs from "Recommender Systems with Generative Retrieval"

This is a collection of flashcard decks created for classes at Karlsruhe Institute of Technology.

Python scripts for studying bias in recommender systems

RecommenderSystems: from 0 to practice. 包括推荐系统实践和深度推荐系统两部分

This GitHub course teaches essential Data Mining skills, including managing large datasets, interpreting relevant data, and applying flexible knowledge to gain expertise in statistic techniques, covering pre-processing, similarity metrics, basket analysis, association rules mining, recommender systems, and streaming data handling.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Deep Learning for Recommender Systems leverages neural networks to analyze user data and provide accurate, personalized recommendations, enhancing user experience and engagement across platforms.

This is the official repository of "EDGE-Rec: Efficient and Data-Guided Edge Diffusion for Recommender System Graphs" (GenAIRecP @ KDD 2024)

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Deep Learning for Recommendation in E-Commerce leverages neural networks to analyze customer data and generate personalized product suggestions, enhancing user experience and increasing business revenue.

Includes Source Code, PPT, Synopsis, Report, Documents, Base Research Paper & Video tutorials. Deep Learning for Recommender Systems leverages neural networks to analyze user data and provide accurate, personalized recommendations, enhancing user experience and engagement across platforms.

🌟 Create dynamic agent-based simulations with Mini-Massive, a lightweight framework for crafting swarms, crowds, and more, inspired by Weta Digital’s Massive.

A recommendation system leveraging similarity measures to generate top-N item recommendations for various applications..

# 🔍 Semantic Article RecommenderThis project offers a simple way to find articles that are similar in meaning. It uses advanced techniques like Hugging Face embeddings and FAISS for efficient searching. 🛠️