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.
A Python implementation of LightFM, a hybrid recommendation algorithm.
Papers on Computational Advertising
Fast Python Collaborative Filtering for Implicit Feedback Datasets
Classic papers and resources on recommendation
Accelerated deep learning R&D
Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps!
Deep recommender models using PyTorch.
A Deep Learning Recommender System
Recommender Learning with Tensorflow2.x
TensorFlow Recommenders is a library for building recommender system models using TensorFlow.
Neural Collaborative Filtering
Pytorch domain library for recommendation systems
QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)
A framework for large scale recommendation algorithms.
Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.
A TensorFlow recommendation algorithm and framework in Python.
fastFM: A Library for Factorization Machines
Transformers4Rec is a flexible and efficient library for sequential and session-based recommendation and works with PyTorch.
KGAT: Knowledge Graph Attention Network for Recommendation, KDD2019
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