| transformer-rec | Transformer-based Recommenders |   |
| drl-recsys | Deep Reinforcement Learning in Recommender Systems | |
| sessrec-gnn | Session-based Recommendation with Graph Neural Networks | |
| ope-rec | Off-policy Evaluation in Recommender Systems | |
| incremental-learning | Model Retraining & Incremental Learning in Recommender Systems | |
| multiobjective-optimizations | Multi-Objective Optimizations in Recommender Systems | |
| coldstart-recsys | Proving Recommendations in case of Cold-start situations | |
| recsys-attacks | Attacks on Recommender Systems | |
| graph-embeddings | Graph Embeddings | |
| S138006 | SiReN: Sign-Aware GNN Recommender | |
| S394070 | Deep Variational Models for Collaborative Filtering-based Recommender Systems | |
| S758139 | DRGR: Deep Reinforcement learning based Group Recommender system | |
| S758139 | RL101: Reinforcement Learning Fundamentals | |
| S021355 | Building 15 Matching and Ranking Recommendation Models from scratch in Tensorflow | |
| S486984 | Data Science Basics and Real-world Case Studies | |
| S693545 | Learning Graph Embeddings with HMLET (End) Model | |
| S318140 | IEEE Challenge 2021 Session-aware Recommendation with Transformer | |
| S593234 | Basic Retail Recommender | |
| S691423 | D-Optimal Online Experiment Design for Recommender Selection | |
| S165806 | Group Playlist Recommender | |
| S794944 | LR-GCCF: Graph-based Recommender Model | |
| S516304 | CTR Models in PyTorch | |
| S181315 | SLIST: Session-aware Linear Item-Item Model for Session-based Recommendation | |
| S819118 | Predictability limits in session-based next item recommendation | |
| S883757 | OLX Job Recommender | |
| S873634 | Batch Learning in Stochastic Bandits | |
| S832885 | Entire Item Space Exploration with Contextual Bandits | |
| S241566 | Debiased Explainable Pairwise Ranking from Implicit Feedback | |
| S035564 | Equal Experience in Recommender Systems | |
| S346877 | Graph Meta Network for Multi-Behavior Recommendation | |
| S063707 | Learning Robust Recommender from Noisy Implicit Feedback | |
| S969915 | Self-Supervised Graph Co-Training for Session-based Recommendation | |
| S810511 | Retail Session-based recommendations | |
| S307784 | Real-time event capturing with Kafka and MongoDB | |
| S632684 | Collaborative Filtering Models on MovieLens Dataset | |
| S168471 | GroupIM: A Mutual Information Maximization Framework for Neural Group Recommendation | |
| reconb | 200+ Jupyter Notebooks on Recommender Systems |   |
| recostep | Collection of Recsys Tutorials and Stories | |