Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

Developer-friendly, embedded retrieval engine for multimodal AI. Search More; Manage Less.

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

Deep recommender models using PyTorch.

A Deep Learning Recommender System

Pytorch domain library for recommendation systems

A framework for large scale recommendation algorithms.

Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking (CTR/CVR prediction), Post Ranking, Relevance, LLM, Reinforcement Learning and so on.

TensorFlow Recommenders is a library for building recommender system models using TensorFlow.

Recommender Learning with Tensorflow2.x

Neural Collaborative Filtering

QRec: A Python Framework for quick implementation of recommender systems (TensorFlow Based)

A TensorFlow recommendation algorithm and framework in Python.

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

NVTabular is a feature engineering and preprocessing library for tabular data designed to quickly and easily manipulate terabyte scale datasets used to train deep learning based recommender systems.