Jingwei Zheng

andrej-karpathy-skills. A single CLAUDE.md file to improve Claude Code behavior, derived from Andrej Karpathy's observations on LLM coding pitfalls.

defuddle. Get the main content of any page as Markdown.

nanochat. The best ChatGPT that $100 can buy.

UI-TARS. Pioneering Automated GUI Interaction with Native Agents

fun-rec. 推荐系统入门教程，在线阅读地址：https://datawhalechina.github.io/fun-rec/

ChatLaw. ChatLaw：A Powerful LLM Tailored for Chinese Legal. 中文法律大模型

AI_Tutorial. 大厂发布的AI落地实践、顶尖实验室的最新论文、工业界的真实踩坑记录

PaddleBox. PArallel Distributed Deep LEarning （PaddlePaddle核心框架，高性能单机、分布式训练和跨平台部署）

Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising. Awesome Deep Learning papers for industrial Search, Recommendation and Advertisement. They focus on Embedding, Matching, Pre-Ranking, Ranking, Post Ranking, Relevance, LLM and RL. Please cite our paper "Deep Learning to Rank in Industrial Search Engines, Recommender Systems, and Online Advertising - An Overview and New Perspectives" (TOIS 2026).

PaddleRec. Recommendation Algorithm大规模推荐算法库，包含推荐系统经典及最新算法LR、Wide&Deep、DSSM、TDM、MIND、Word2Vec、Bert4Rec、DeepWalk、SSR、AITM，DSIN，SIGN，IPREC、GRU4Rec、Youtube_dnn、NCF、GNN、FM、FFM、DeepFM、DCN、DIN、DIEN、DLRM、MMOE、PLE、ESMM、ESCMM, MAML、xDeepFM、DeepFEFM、NFM、AFM、RALM、DMR、GateNet、NAML、DIFM、Deep Crossing、PNN、BST、AutoInt、FGCNN、FLEN、Fibinet、ListWise、DeepRec、ENSFM，TiSAS，AutoFIS等，包含经典推荐系统数据集criteo 、movielens等

recommendation_papers. paper collection for recommendation aspet

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

Kashgari. Kashgari is a production-level NLP Transfer learning framework built on top of tf.keras for text-labeling and text-classification, includes Word2Vec, BERT, and GPT2 Language Embedding.

LightGCN. Python

tf2-gnn. TensorFlow 2 library implementing Graph Neural Networks

night. Weekly Go Online Meetup via Bilibili｜Go 夜读｜通过 bilibili 在线直播的方式分享 Go 相关的技术话题，每天大家在微信/telegram/Slack 上及时沟通交流编程技术话题。

hgcn. Hyperbolic Graph Convolutional Networks in PyTorch.

SGC. official implementation for the paper "Simplifying Graph Convolutional Networks"

pytorch-AGNN. Pytorch implementation of the Attention-based Graph Neural Network(AGNN)

DeepMatch. A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors which can be used for ANN search.

DropEdge. This is a Pytorch implementation of paper: DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

fucking-algorithm. Crack LeetCode, not only how, but also why.

Recommender-System. A developing recommender system in tensorflow2. Algorithm: UserCF, ItemCF, LFM, SLIM, GMF, MLP, NeuMF, FM, DeepFM, MKR, RippleNet, KGCN and so on.

DeepRec. 推荐、广告工业界经典以及最前沿的论文、资料集合/ Must-read Papers on Recommendation System and CTR Prediction

AS-GCN. tensorflow-as-gcn

CS-GNN. Measuring and Improving the Use of Graph Information in Graph Neural Networks

dgi. TensorFlow implementation of Deep Graph Infomax

DGI. Deep Graph Infomax (https://arxiv.org/abs/1809.10341)

ClusterGCN. A PyTorch implementation of "Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional Networks" (KDD 2019).

pyHGT. Code for "Heterogeneous Graph Transformer" (WWW'20), which is based on pytorch_geometric

multi-armed-bandit. Play with the solutions to the multi-armed-bandit problem.

transformer-tensorflow. Implementation of Transformer Model in Tensorflow

P-GNN. Position-aware Graph Neural Networks

Awesome-RecSystem-Models. Implements of Awesome RecSystem Models with PyTorch/TF2.0

NeuRec. Next RecSys Library

interaction-aware-factorization-machines. Tensorflow implementation for Interaction-aware factorization machines

CapsGNN. A PyTorch implementation of "Capsule Graph Neural Network" (ICLR 2019).

Graph-Bert. Source code of Graph-Bert

geom-gcn. Python

outline-apps. Outline Client and Manager, developed by Jigsaw. Outline Manager makes it easy to create your own VPN server. Outline Client lets you share access to your VPN with anyone in your network, giving them access to the free and open internet.

GraphSAINT. [ICLR 2020; IPDPS 2019] Fast and accurate minibatch training for deep GNNs and large graphs (GraphSAINT: Graph Sampling Based Inductive Learning Method).

awesome-multimodal-ml. Reading list for research topics in multimodal machine learning

AutoInt. Implementation of AutoInt: Automatic Feature Interaction Learning via Self-Attentive Neural Networks

serving. A flexible, high-performance serving system for machine learning models

Recommend-Estimators. Classical RecSys algorithms implemented by using TensorFlow Estimators

neural_factorization_machine. TenforFlow Implementation of Neural Factorization Machine

Summary-of-Recommender-System-Papers. 阅读过的推荐系统论文的归类总结，持续更新中…

MVE. C++

SR-GNN. [AAAI 2019] Source code and datasets for "Session-based Recommendation with Graph Neural Networks"

linear_graph_autoencoders. Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)

Fi_GNN. [CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"

GraphEmbedding. Implementation and experiments of graph embedding algorithms.

MixHop-and-N-GCN. An implementation of "MixHop: Higher-Order Graph Convolutional Architectures via Sparsified Neighborhood Mixing" (ICML 2019).

GATE. Graph Attention Auto-Encoders

APPNP. A PyTorch implementation of "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019).

APNE. Code of the paper "Enhancing Network Embedding with Auxiliary Information: An Explicit Matrix Factorization Perspective"

graphRNN. Codes for the paper "Learning Graph-Level Representations with Gated Recurrent Neural Networks"

GEMSEC. The TensorFlow reference implementation of 'GEMSEC: Graph Embedding with Self Clustering' (ASONAM 2019).

GRAF. Inner product natural graph factorization machine used in 'GEMSEC: Graph Embedding with Self Clustering' .

SINE. A PyTorch Implementation of "SINE: Scalable Incomplete Network Embedding" (ICDM 2018).

leedl-tutorial. 《李宏毅深度学习教程》（李宏毅老师推荐👍，苹果书🍎），PDF下载地址：https://github.com/datawhalechina/leedl-tutorial/releases

SimGNN. Python

FeatWalk_AAAI19. Large-Scale Heterogeneous Feature Embedding

TEA. Triplet Enhanced AutoEncoder: Model-free Discriminative Network Embedding

AAANE. Python

transformers. 🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

MUSAE. The reference implementation of "Multi-scale Attributed Node Embedding". (Journal of Complex Networks 2021)

LiteratureDL4Graph. A comprehensive collection of recent papers on graph deep learning

KGNN-LS. A tensorflow implementation of Knowledge-aware Graph Neural Networks with Label Smoothness regularization

H-GCN. [IJCAI 2019] Source code and datasets for "Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification"

x-deeplearning. An industrial deep learning framework for high-dimension sparse data

GRU4Rec_TensorFlow. TensorFlow implemenation of GRu4Rec model

RecommenderSystems. Python

DeepInterestNetwork. Python

dien. Python

stanford-tensorflow-tutorials. This repository contains code examples for the Stanford's course: TensorFlow for Deep Learning Research.

faiss. A library for efficient similarity search and clustering of dense vectors.

nsg. Navigating Spreading-out Graph For Approximate Nearest Neighbor Search

interview_python. 关于Python的面试题

lihang-code. 《统计学习方法》的代码实现

google-research. Google Research

dlrm. An implementation of a deep learning recommendation model (DLRM)

HINE. Heterogeneous Information Network Embedding

dnn_ctr. The framework to deal with ctr problem。The project contains FNN,PNN,DEEPFM, NFM etc

CTR_Prediction. CTR prediction using FM FFM and DeepFM

nndl-practice. 邱锡鹏《神经网络与深度学习：案例与实践》PyTorch 实现

numpy-ml. Machine learning, in numpy

Attention_Network_With_Keras. An example attention network with simple dataset.

mlbasic. 深度学习常用优化方法详解

algo. 数据结构和算法必知必会的50个代码实现

Lihang. Statistical learning methods, 统计学习方法(第2版)[李航] [笔记, 代码, notebook, 参考文献, Errata, lihang]

hadoop-cluster-docker. Run Hadoop Custer within Docker Containers

hadoop-book. Example source code accompanying O'Reilly's "Hadoop: The Definitive Guide" by Tom White

GraRep. A SciPy implementation of "GraRep: Learning Graph Representations with Global Structural Information" (WWW 2015).

role2vec. A scalable Gensim implementation of "Learning Role-based Graph Embeddings" (IJCAI 2018).

STAR-GCN. STAR-GCN: Stacked and Reconstructed Graph Convolutional Networks for Recommender Systems

smore. SMORe: Modularize Graph Embedding for Recommendation

HAN. Heterogeneous Graph Neural Network

CTR-Prediction. Sharing the CTR Prediction original paper and personal study notes

ASNE. Tensorflow implementation of Attributed Social Network Embedding framework (ASNE)

ANRL. ANRL: Attributed Network Representation Learning via Deep Neural Networks(IJCAI-2018)

neural_collaborative_filtering. Neural Collaborative Filtering

CAN. Co-embedding Attributed Networks

GATNE. Source code and dataset for KDD 2019 paper "Representation Learning for Attributed Multiplex Heterogeneous Network"

LANE. Label Informed Attributed Network Embedding, WSDM 2017

GAT2VEC. embedding attributed graphs

DANE. Python

spine. Code of the paper "SPINE: Structural Identity Preserved Inductive Network Embedding"

MachineLearning. Basic Machine Learning and Deep Learning

tensorflow2_tutorials_chinese. tensorflow2中文教程，持续更新(当前版本:tensorflow2.0)，tag: tensorflow 2.0 tutorials

librec. LibRec: A Leading Java Library for Recommender Systems, see

neural_graph_collaborative_filtering. Neural Graph Collaborative Filtering, SIGIR2019

Graph2Seq. Graph2Seq is a simple code for building a graph-encoder and sequence-decoder for NLP and other AI/ML/DL tasks.

BiNE. BiNE: Bipartite Network Embedding

Seminar-Materials. 组会ppt与论文--每一次的精心准备都值得留下记录😛

text_gcn. Graph Convolutional Networks for Text Classification. AAAI 2019

leetcode. LeetCode Solutions: A Record of My Problem Solving Journey.( leetcode题解，记录自己的leetcode解题之路。)

pumpkin-book. 南瓜书：《机器学习》（西瓜书）公式详解

PyTorch-BigGraph. Generate embeddings from large-scale graph-structured data.

DeepCTR. Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

tensorflow-tutorial. Example TensorFlow codes and Caicloud TensorFlow as a Service dev environment.

Youtube-Recommendation-Tensorflow. code of paper `Deep Neural Networks for Youtube Recommendation`

NTU_HYLee_MachineLearning_Homework. 作業分享：台大李宏毅 (Hung-Yi Lee) 教授的Machine Learning (2016, Fall)

SDNE. This is a implementation of SDNE (Structural Deep Network embedding)

rtb-papers. A collection of research and survey papers of real-time bidding (RTB) based display advertising techniques.

Reco-papers. Classic papers and resources on recommendation

AI-Job-Notes. AI算法岗求职攻略（涵盖准备攻略、刷题指南、内推和AI公司清单等资料）

quick-SQL-cheatsheet. A quick reminder of all SQL queries and examples on how to use them.

xlearn. High performance, easy-to-use, and scalable machine learning (ML) package, including linear model (LR), factorization machines (FM), and field-aware factorization machines (FFM) for Python and CLI interface.

deep_learning. 基础的深度学习实验研究结果汇总笔记

RSAlgorithms. RSTutorials: A Curated List of Algorithms about Traditional and Social Recommender System.

kaggle_criteo_ctr_challenge-. This is a kaggle challenge project called Display Advertising Challenge by CriteoLabs at 2014.这是2014年由CriteoLabs在kaggle上发起的广告点击率预估挑战项目。

tensorflow-DeepFM. Tensorflow implementation of DeepFM for CTR prediction.

euler. A distributed graph deep learning framework.

irgan. IRGAN SIGIR paper experimental code

CodingInterviewChinese2. 《剑指Offer：名企面试官精讲典型编程面试题》第二版源代码

RSPapers. RSTutorials: A Curated List of Must-read Papers on Recommender System.

zhihu. This repo contains the source code in my personal column (https://zhuanlan.zhihu.com/zhaoyeyu), implemented using Python 3.6. Including Natural Language Processing and Computer Vision projects, such as text generation, machine translation, deep convolution GAN and other actual combat code.

GNNPapers. Must-read papers on graph neural networks (GNN)

echarts. Apache ECharts is a powerful, interactive charting and data visualization library for browser

Exponential-histogram. An important and widely used model for streaming data

SlidingBloomfilter-Sketch. Summarize streaming data over sliding windows

Splitter-Windowed-CountMin. An on-line algorithms that efficiently estimate frequencies in the active window over streaming data.

GEM. Python

TADW. Network Representation Learning with Rich Text Information (IJCAI 2015)

snap. Stanford Network Analysis Platform (SNAP) is a general purpose network analysis and graph mining library.

HEER. Easing Embedding Learning by Comprehensive Transcription of Heterogeneous Information Networks(KDD'18)

verse. Reference implementation of the paper VERSE: Versatile Graph Embeddings from Similarity Measures

mgcnn. Multi-Graph Convolutional Neural Networks

awesome-graph-classification. A collection of important graph embedding, classification and representation learning papers with implementations.

awesome-network-embedding. A curated list of network embedding techniques.

horovod. Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet.

fm_tensorflow. Factorization Machines implementation with Tensorflow

TensorFlow-Examples. TensorFlow Tutorial and Examples for Beginners (support TF v1 & v2)

statistical-learning-method. 李航《统计学习方法》算法python实现以及sk-learn实现

resume. :space_invader: My resume / 我的简历

awesome-neue-latex-cv-extended. Latex CV template built with Font Awesome and Adobe Source Font. Originally based on Alessandro Plasmati's CV template.

yaac-another-awesome-cv. YAAC: Another Awesome CV is a template using Font Awesome and Adobe Source Font.

Awesome-CV. :page_facing_up: Awesome CV is LaTeX template for your outstanding job application

resume. An elegant \LaTeX\ résumé template. 大陆镜像 https://gods.coding.net/p/resume/git

TensorFlow-cn. 简单粗暴 TensorFlow (1.X) | A Concise Handbook of TensorFlow (1.X) | 此版本不再更新，新版见 https://tf.wiki

line. TensorFlow implementation of paper "LINE: Large-scale Information Network Embedding" by Jian Tang, et al.

word2vec. Automatically exported from code.google.com/p/word2vec

FastGCN. The sample codes for our ICLR18 paper "FastGCN: Fast Learning with Graph Convolutional Networks via Importance Sampling""

node2vec. Scala

machinelearning. My blogs and code for machine learning. http://cnblogs.com/pinard

word2vec. Python interface to Google word2vec

struc2vec. This repository provides a reference implementation of struc2vec.

DeepLearning-500-questions. 深度学习500问，以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述，以帮助自己及有需要的读者。 全书分为18个章节，50余万字。由于水平有限，书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作，联系scutjy2015@163.com 版权所有，违权必究 Tan 2018.06

HARP. Code for the AAAI 2018 Paper "HARP: Hierarchical Representation Learning for Networks"

TransNet. Source code and datasets of IJCAI2017 paper "TransNet: Translation-Based Network Representation Learning for Social Relation Extraction".

KRLPapers. Must-read papers on knowledge representation learning (KRL) / knowledge embedding (KE)

Graph-Capsule-CNN-Networks. Graph Capsule Convolutional Neural Networks

gc-mc. Python

pygcn. Graph Convolutional Networks in PyTorch

ZipNet-GAN-traffic-inference. Python

OpenNE. An Open-Source Package for Network Embedding (NE)

tensorflow_practice. tensorflow实战练习，包括强化学习、推荐系统、nlp等

joy. A package for capturing and analyzing network flow data and intraflow data, for network research, forensics, and security monitoring.

Deep-Learning-Roadmap. :satellite: Organized Resources for Deep Learning Researchers and Developers

NRLPapers. Must-read papers on network representation learning (NRL) / network embedding (NE)

GraphSAGE. Representation learning on large graphs using stochastic graph convolutions.

graph-generation. GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models

nndl. 邱锡鹏《神经网络与深度学习》（蒲公英书）理论书 v2 与通识版

GAT. Graph Attention Networks (https://arxiv.org/abs/1710.10903)

C-Plus-Plus. Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

Python. All Algorithms implemented in Python

Comprehensive-analysis-of-network-traffic-data. Code resource (R) for the paper: https://onlinelibrary.wiley.com/doi/abs/10.1002/cpe.4181

ML-SDN. My codes

MULTI. Machine-Learning for Traffic Identification

awesome-public-datasets. A topic-centric list of HQ open datasets.

wireshark-ntop. Extensions for Wireshark

nDPI. Open Source Deep Packet Inspection Software Toolkit

TensorFlow-Deep-Learning. 用TensorFlow搭建CNN/RNN/LSTM/GRU/BiRNN/BiLSTM/BiGRU/Capsule Network等deep learning模型

SketchML. Accelerating Distributed Machine Learning with Data Sketches

pytorch-tutorial. PyTorch Tutorial for Deep Learning Researchers

Tensorflow-Programs-and-Tutorials. Implementations of CNNs, RNNs, GANs, etc

interview. 笔试面试知识整理

planetoid. Semi-supervised learning with graph embeddings

NRI. Neural relational inference for interacting systems - pytorch