AhanWhite's Stars
jwasham/coding-interview-university
A complete computer science study plan to become a software engineer.
TheAlgorithms/Python
All Algorithms implemented in Python
kdn251/interviews
Everything you need to know to get the job.
QSCTech/zju-icicles
浙江大学课程攻略共享计划
gto76/python-cheatsheet
Comprehensive Python Cheatsheet
halo-dev/halo
强大易用的开源建站工具。
PKUanonym/REKCARC-TSC-UHT
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
lib-pku/libpku
贵校课程资料民间整理
wuyouzhuguli/SpringAll
循序渐进,学习Spring Boot、Spring Boot & Shiro、Spring Batch、Spring Cloud、Spring Cloud Alibaba、Spring Security & Spring Security OAuth2,博客Spring系列源码:https://mrbird.cc
hollischuang/toBeTopJavaer
To Be Top Javaer - Java工程师成神之路
zhaoolee/ChromeAppHeroes
🌈谷粒-Chrome插件英雄榜, 为优秀的Chrome插件写一本中文说明书, 让Chrome插件英雄们造福人类~ ChromePluginHeroes, Write a Chinese manual for the excellent Chrome plugin, let the Chrome plugin heroes benefit the human~ 公众号「0加1」同步更新
taizilongxu/interview_python
关于Python的面试题
USTC-Resource/USTC-Course
:heart:中国科学技术大学课程资源
b3log/solo
仓库已经迁移到 https://github.com/88250/solo
mJackie/RecSys
计算广告/推荐系统/机器学习(Machine Learning)/点击率(CTR)/转化率(CVR)预估/点击率预估
HaoZhang95/Python24
网上搜集的自学python语言的资料集合,包括整套代码和讲义集合,这是至今为止所开放网上能够查找到的最新视频教程,网上找不到其他最新的python整套视频了,. 具体的无加密的mp4视频教程和讲义集合可以在更新的Readme文件中找到,下载直接打开就能播放,项目从零基础的Python教程到深度学习,总共30章节,其中包含Python基础中的飞机大战项目,WSGI项目,Flask新经资讯项目, Django的电商项目(本应该的美多商城项目因为使用的是Vue技术,所以替换为Django天天生鲜项目)等等,希望能够帮助大家。资源搜集劳神费力,能帮到你的话是我的福分,望大家多多支持,喜欢本仓库的话,记得Star哦。
ycjuan/kaggle-2014-criteo
Trinkle23897/THU-CST-Cracker
清华大学计算机系课程攻略 Guidance for courses in Department of Computer Science and Technology, Tsinghua University
HttpErrorPages/HttpErrorPages
:fast_forward: Simple HTTP Error Page Generator
giscafer/FinalScheduler
:calendar: 终极排班管理、考勤系统
confucianzuoyuan/bookstore
使用Django编写一个书城电商网站,配合详细的教程。
cuke-ui/cuke-ui
🥒 黄瓜ui:一个即插即用的React UI 库
songxiaoliang/ComicApp
[停止维护] 基于 ReactNative、Redux 的漫画书App,支持Android、iOS 平台.
jgchenu/open-blog
记录找实习期间整理的一些文件,搬运请注明出处,谢谢
shuaijia/JsHeadline
仿头条
ivanliu1989/Predict-click-through-rates-on-display-ads
Display advertising is a billion dollar effort and one of the central uses of machine learning on the Internet. However, its data and methods are usually kept under lock and key. In this research competition, CriteoLabs is sharing a week’s worth of data for you to develop models predicting ad click-through rate (CTR). Given a user and the page he is visiting, what is the probability that he will click on a given ad? The goal of this challenge is to benchmark the most accurate ML algorithms for CTR estimation. All winning models will be released under an open source license. As a participant, you are given a chance to access the traffic logs from Criteo that include various undisclosed features along with the click labels.
yangchangkui/schedule
值日排班系统
cumtfc/shadowsocksr
Python port of ShadowsocksR
chenhaoxiang/996.ICU
Repo for counting stars and contributing. Press F to pay respect to glorious developers.
chenhaoxiang/JavaGuide
【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。