maosengshulei

Modern-CPP-Programming

Modern C++ Programming Course (C++03/11/14/17/20/23/26)

redis-3.0-annotated

带有详细注释的 Redis 3.0 代码（annotated Redis 3.0 source code）。

EffectiveModernCppChinese

《Effective Modern C++》- 完成翻译

tiny-cuda-nn

Lightning fast C++/CUDA neural network framework

GraphSAGE

Representation learning on large graphs using stochastic graph convolutions.

AI-System

System for AI Education Resource.

MIT6.S081

Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

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.

animatediff-cli-prompt-travel

animatediff prompt travel

RecSysPapers

推荐/广告/搜索领域工业界经典以及最前沿论文集合。A collection of industry classics and cutting-edge papers in the field of recommendation/advertising/search.

DeepRec

DeepRec is a high-performance recommendation deep learning framework based on TensorFlow. It is hosted in incubation in LF AI & Data Foundation.

HugeCTR

HugeCTR is a high efficiency GPU framework designed for Click-Through-Rate (CTR) estimating training

FuxiCTR

A configurable, tunable, and reproducible library for CTR prediction https://fuxictr.github.io

autofaiss

Automatically create Faiss knn indices with the most optimal similarity search parameters.

datrie

Fast, efficiently stored Trie for Python. Uses libdatrie.

GraphGallery

GraphGallery is a gallery for benchmarking Graph Neural Networks, From InplusLab.

GNN-FakeNews

A collection of GNN-based fake news detection models.

RecDebiasing

This repository collects debiasing methods for recommendation

mlspace

MLSpace: Hassle-free machine learning & deep learning development

eecs598

Advanced Topics on Systems for X

SmallPebble

Minimal deep learning library written from scratch in Python, using NumPy/CuPy.

Super-Mario-RL

🍄Reinforcement Learning: Super Mario Bros with dueling dqn🍄

learnable-embed-sizes-for-RecSys

A PyTorch implementation of ICLR 2021 paper: Learnable Embedding Sizes for Recommender Systems

MetaHeac

This is an official implementation for "Learning to Expand Audience via Meta Hybrid Experts and Critics for Recommendation and Advertising"(KDD2021).

autogen

Autogenic differentiation

causal-recsys-public

BEBR

Official code for "Binary embedding based retrieval at Tencent"

multi-task_loss_optimizer

Implement the Pareto Optimizer and pcgrad to make a self-adaptive loss for multi-task

InterHAt

This is the repository for our WSDM 2020 publication: Interpretable Click-through Rate Prediction through Hierarchical Attention

ASMG