🔥简洁易用的C++11网络库 / 支持单机千万并发连接 / a simple C++11 network server framework

模拟Linux文件系统

An example kernel filesystem implementation

类Unix文件系统设计与实现 二级文件系统

我的操作系统课程设计，实现一个类似unix的文件系统。

C++11 Lightweight Redis client: async, thread-safe, no dependency, pipelining, multi-platform - NO LONGER MAINTAINED - Please check https://github.com/cpp-redis/cpp_redis

A novel spatio-temporal adaptive graph convolutional network model (STAGCN) based on deep learning

Graph CNNs for population graphs

A list of learning materials to understand databases internals

带有详细注释，配有相应博客讲解，适合用于学习STL、数据结构算法的简易STL库。

Algorithms & Data structures in C++.

C++ Design Patterns

ASD detection using machine and deep learning for a course project. Various models have been compared in detecting ASD from the obtained dataset of fMRI brain scans.

In this project preprocessed MRI and fMRI data are used to implement Random Forest (RF) and Support Vector Machine (SVM) classifiers to diagnose ASD patients.

fMRI analysis pipeline

Classifying ADHD fMRI data with a CNN+LSTM Model

Pytorch implementation of pooling-regularized GNN (PRGNN) for fMRI analysis. https://arxiv.org/pdf/2007.14589.pdf

List of ressources and practicals used for the fMRI data analysis course of UoB (UK) (2014-2017)

Brain decoding using graph convolutional network on fMRI time-series

Code for 2nd edition of fMRI analysis handbook

Code for processing and analysis of resting state fMRI

Materials from fMRI data analysis course for cognitive science students.

QT实现的学生信息管理系统，高程大作业

C++实践 使用Qt实现了简单的分角色登陆的学生信息管理系统

stackoverflow 上对 C/C++ 问题的整理、总结和翻译。

Deep Learning papers reading roadmap for anyone who are eager to learn this amazing tech!

信号处理 时域、频域、功率谱密度、自相关分析 Time Domain analysis, Frequency Domain analysis, Power Spectrum Density and Autocorrelation Analysis

Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning.ai: (i) Neural Networks and Deep Learning; (ii) Improving Deep N…

AI Roadmap:机器学习(Machine Learning)、深度学习(Deep Learning)、对抗神经网络(GAN），图神经网络（GNN），NLP，大数据相关的发展路书(roadmap), 并附海量源码（python，pytorch）带大家消化基本知识点，突破面试，完成从新手到合格工程师的跨越，其中深度学习相关论文附有tensorflow caffe官方源码，应用部分含推荐算法…

深度学习论文翻译，包括分类论文，检测论文等