Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
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Updated
May 22, 2024 - Python
Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.
Papers on Computational Advertising
A Deep Learning Recommender System
Classic papers and resources on recommendation
A Python implementation of LightFM, a hybrid recommendation algorithm.
Neural Collaborative Filtering
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Recommender Learning with Tensorflow2.x
Deep recommender models using PyTorch.
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
Accelerated deep learning R&D
Pytorch domain library for recommendation systems
A django website used in the book Practical Recommender Systems to illustrate how recommender algorithms can be implemented.
A wine recommender system tutorial using Python technologies such as Django, Pandas, or Scikit-learn, and others such as Bootstrap.
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
YEDDA: A Lightweight Collaborative Text Span Annotation Tool. Code for ACL 2018 Best Demo Paper Nomination.
A framework for large scale recommendation algorithms.
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Neural Graph Collaborative Filtering, SIGIR2019
This is the repository of our article published in RecSys 2019 "Are We Really Making Much Progress? A Worrying Analysis of Recent Neural Recommendation Approaches" and of several follow-up studies.
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