#Recommender-systems
Showing 24 of 24 repositories tagged #recommender-systems, ranked by stars
State-of-the-Art Deep Learning scripts organized by models - easy to train and deploy with reproducible accuracy and performance on enterprise-grade infrastructure.
A unified, comprehensive and efficient recommendation library
大厂发布的AI落地实践、顶尖实验室的最新论文、工业界的真实踩坑记录
Learning to Rank in TensorFlow
Survey: A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.
An Open-source Toolkit for Deep Learning based Recommendation with Tensorflow.
This is a repository of a topic-centric public data sources in high quality for Recommender Systems (RS)
Learn about Machine Learning and Artificial Intelligence
[AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"
[WSDM'2024 Oral] "SSLRec: A Self-Supervised Learning Framework for Recommendation"
pytorch version of neural collaborative filtering
Deep Learning Computer Vision Algorithms for Real-World Use
Succinct Machine Learning algorithm implementations from scratch in Python, solving real-world problems (Notebooks and Book). Examples of Logistic Regression, Linear Regression, Decision Trees, K-means clustering, Sentiment Analysis, Recommender Systems, Neural Networks and Reinforcement Learning.
A tutorial series by Preferred.AI
Daily notes on AI papers
Samantha - A generic recommender and predictor server
A world wines dataset with user ratings for recommendation systems and general use.
It is a blueprint to data science from the mathematics to algorithms. It is not completed.
Kickstart AI through Machine Learning and Deep Learning Projects (20+)
This is the repo for the survey of Bias and Fairness in IR with LLMs.
Contains code which covers various methods for recommending movies, some of the methods include matrix factorisation , deep learning based recommendation systems
Movie Recommendation System: Project using R and Machine learning
Learning PyTorch through the D2L book. A series of notebooks for the same
An Exploratory Toolkit for Recommender Systems Datasets and Splits