- https://medium.datadriveninvestor.com/how-to-build-a-recommendation-system-for-purchase-data-step-by-step-d6d7a78800b6
- https://www.kaggle.com/c/santander-product-recommendation
- https://www.kaggle.com/retailrocket/ecommerce-dataset/home
- https://www.kaggle.com/dschettler8845/recsys-2020-ecommerce-dataset/tasks?taskId=3124
- https://www.kaggle.com/sohamohajeri/recommendation-system-for-electronic-dataset
- https://towardsdatascience.com/extreme-deep-factorization-machine-xdeepfm-1ba180a6de78
- https://medium.com/building-creative-market/word2vec-inspired-recommendations-in-production-f2c6a6b5b0bf
- https://medium.com/shoprunner/fetching-better-beer-recommendations-with-collie-part-1-18c73ab30fbd
- https://towardsdatascience.com/deep-dive-into-netflixs-recommender-system-341806ae3b48
- Modern Recommender Systems. - A Deep Dive into the AI algorithms [Jun 2021]
- pytorch-for-recommenders-101 [Apr 2018]
- Deep Learning Recommendation Models (DLRM) : A Deep Dive [Oct 2020]
- deep-learning-recommendation-models-dlrm-deep-dive [Apr 2021]
- https://towardsdatascience.com/modern-recommender-systems-a0c727609aa8
- https://towardsdatascience.com/how-to-build-a-strong-baseline-recommender-using-pytorch-on-a-regular-laptop-2ad497504fe6
- https://towardsdatascience.com/recommender-systems-using-deep-learning-in-pytorch-from-scratch-f661b8f391d7
- https://www.cs.toronto.edu/~amnih/papers/bpmf.pdf
- https://towardsdatascience.com/probabilistic-matrix-factorization-b7852244a321
- https://docs.pymc.io/notebooks/probabilistic_matrix_factorization.html
- https://medium.com/@judaikawa/building-and-evaluating-a-recommender-system-for-implicit-feedback-59495d2077d4
- https://www.kaggle.com/c/instacart-market-basket-analysis/data
- https://towardsdatascience.com/factorization-machines-for-item-recommendation-with-implicit-feedback-data-5655a7c749db
- Network models for recommender systems | by Roxana Pamfil | dunnhumby Data Science & Engineeringhttps://medium.com/dunnhumby-data-science-engineering/network-models-for-recommender-systems-7f0d6d210ccf
- https://medium.com/genifyai/genify-transformer-model-recommender-system-6cd0c8414527
- https://blog.fastforwardlabs.com/2018/01/22/exploring-recommendation-systems.html
How Variational Autoencoders make classical recommender systems obsolete.
- https://taufik-azri.medium.com/recommendation-system-for-retail-customer-3f0f80b84221
- Spotify - https://www.univ.ai/post/spotify-recommendations
- https://colab.research.google.com/github/google/eng-edu/blob/main/ml/recommendation-systems/recommendation-systems.ipynb
- Part 1: An Executive Guide to Building Recommendation System
- Part 2: The 10 Categories of Deep Recommendation Systems That…
- Part 3: The 6 Research Directions of Deep Recommendation Systems That…
- Part 4: The 7 Variants of MF For Collaborative Filtering
- Part 5: The 5 Variants of MLP for Collaborative Filtering
- Part 6: The 6 Variants of Autoencoders for Collaborative Filtering
- https://github.com/lyst/lightfm
- https://github.com/benfred/implicit
- https://github.com/maciejkula/spotlight
- https://github.com/shenweichen/DeepCTR
- https://github.com/etlundquist/rankfm
- https://github.com/tensorflow/recommenders quick start
- https://github.com/jfkirk/tensorrec
- https://github.com/tensorflow/ranking/
- https://github.com/RUCAIBox/RecBole
- https://github.com/ShopRunner/collie_recs/
- https://www.kaggle.com/retailrocket/ecommerce-dataset
- https://gist.github.com/entaroadun/1653794
- https://github.com/RUCAIBox/RecSysDatasets
Papers