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6.s081-all-in-one

6.S081课程全记录，包括课程使用的书籍、论文、实验要求的中文翻译，以及实验过程记录

android-yolo

Real-time object detection on Android using the YOLO network with TensorFlow

assemblylanguagetest

王爽《汇编语言》第三版课后实验及检测点答案。

cgdb

Console front-end to the GNU debugger

community

computer-networking-a-top-down-approach-notes

《计算机网络－自顶向下方法(原书第6版)》编程作业，Wireshark实验文档的翻译和解答。

cooperative-multi-agent-reinforcement-learning-for-low-level-wireless-communication

Spring 2017 Deep Reinforcement Learning Final Project

cplusplusthings

C++那些事

cppprimerplus-six-

C++PrimerPlus(第6版)中文版源码

cs-notes

:books: Tech Interview Guide 技术面试必备基础知识、Leetcode 题解、Java、C++、Python、后端面试、操作系统、计算机网络、系统设计

d-amp_toolbox

This package contains the code to run Learned D-AMP, D-AMP, D-VAMP, D-prGAMP, and DnCNN algorithms. It also includes code to train Learned D-AMP, DnCNN, and Deep Image Prior U-net using the SURE loss.

deep-learning-papers-translation

深度学习论文翻译，包括分类论文，检测论文等

deep_mimo

Unofficial Pytorch implementation of Deep Learning-Based MIMO Communications (Timothy J. O’Shea)

drawio

end2end_gan

Conditional GAN based End-to-End Communication System

faster-rcnn.pytorch

A faster pytorch implementation of faster r-cnn

fucking-algorithm

手把手撕LeetCode题目，扒各种算法套路的裤子。English version supported! Crack LeetCode, not only how, but also why.

github.io

gnnpapers

Must-read papers on graph neural networks (GNN)

go-books

Books about Nodejs, Angular2, Agile, Clean Code, Docker, Golang, Microservices, REST, TDD, BDD, and Startups.

incubator-brpc

brpc is an Industrial-grade RPC framework using C++ Language, which is often used in high performance system such as Search, Storage, Machine learning, Advertisement, Recommendation etc. "brpc" means "better RPC".

java

存放JAVA开发的设计**、算法：《剑指Offer》、《编程珠玑》、《深入理解Java虚拟机：JVM高级特性与最佳实践》、《重构-改善既有代码的设计 中文版》、《clean_code(中文完整版)》、《Java编程**(第4版)》、《Java核心技术 卷I (第8版)》、《Quartz_Job+Scheduling_Framework》；一些大的上传不上来的文件在README

json-tutorial

从零开始的 JSON 库教程

leetcode

lihang-code

《统计学习方法》的代码实现

linux-0.12

《Linux内核完全剖析》linux0.12源码及实验环境

linux-0.12mtj

linux-2.6.11.12

linux内核源码

maml

Code for "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"

meta-autoencoder

Code for the paper "Meta-Learning to Communicate: Fast End-to-End Training for Fading Channels"