Short Python code snippets for all your development needs

Official repo for the #tidytuesday project

What the f*ck Python? 😱

List of Computer Science courses with video lectures.

My notes of Clean Code book

100+ open-source clones of popular sites like Airbnb, Amazon, Instagram, Netflix, Tiktok, Spotify, Whatsapp, Youtube etc. See source code, demo links, tech stack, github stars.

A collection of algorithms and data structures

Play with fluids in your browser (works even on mobile)

Code from live exploratory analyses of data in R

Design patterns implemented in Java

「Java学习+面试指南」一份涵盖大部分 Java 程序员所需要掌握的核心知识。准备 Java 面试，首选 JavaGuide！

Official code for "InfoGraph: Unsupervised and Semi-supervised Graph-Level Representation Learning via Mutual Information Maximization" (ICLR 2020, spotlight)

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

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

🛁 Clean Code concepts adapted for JavaScript

Papers about pretraining and self-supervised learning on Graph Neural Networks (GNN).

PPNP & APPNP models from "Predict then Propagate: Graph Neural Networks meet Personalized PageRank" (ICLR 2019)

A PyTorch implementation of GraphSAGE. This package contains a PyTorch implementation of GraphSAGE.

Universal Graph Transformer Self-Attention Networks (TheWebConf WWW 2022) (Pytorch and Tensorflow)

Short React code snippets for all your development needs

A PyTorch implementation of "Graph Wavelet Neural Network" (ICLR 2019)

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

Inductive graph-based matrix completion (IGMC) from "M. Zhang and Y. Chen, Inductive Matrix Completion Based on Graph Neural Networks, ICLR 2020 spotlight".

Experimental results obtained with the MinCutPool layer as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling"

VIP cheatsheets for Stanford's CME 102 Ordinary Differential Equations for Engineers

Study guides for MIT's 15.003 Data Science Tools

Strategies for Pre-training Graph Neural Networks

PyTorch Implementation and Explanation of Graph Representation Learning papers: DeepWalk, GCN, GraphSAGE, ChebNet & GAT.

GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training @ KDD 2020

Code samples for my book "Neural Networks and Deep Learning"