jtudjwh Goto Github PK
Type: User
jtudjwh's Projects
machine-learning
some ml demo(based on sklearn)
mnbvc
MNBVC(Massive Never-ending BT Vast Chinese corpus)超大规模中文语料集。对标chatGPT训练的40T数据。MNBVC数据集不但包括主流文化，也包括各个小众文化甚至火星文的数据。MNBVC数据集包括新闻、作文、小说、书籍、杂志、论文、台词、帖子、wiki、古诗、歌词、商品介绍、笑话、糗事、聊天记录等一切形式的纯文本中文数据。
mobike-crawler
摩拜单车爬虫
newsspider
爬取今日头条，网易，腾讯等新闻,并建立简单的搜索引擎
node-chatgpt-api
A client implementation for ChatGPT and Bing AI. Available as a Node.js module, REST API server, and CLI app.
ontts
科大讯飞语音linux在线语音合成后台服务
opendpi
OpenDPI v.3.10
opensips
OpenSIPS is a GPL implementation of a multi-functionality SIP Server that targets to deliver a high-level technical solution (performance, security and quality) to be used in professional SIP server platforms.
openwpm
A web privacy measurement framework
pay-java-parent
第三方支付对接全能支付Java开发工具包.优雅的轻量级支付模块集成支付对接支付整合（微信,支付宝,银联,友店,富友,跨境支付paypal,payoneer(P卡派安盈)易极付）app,扫码,网页刷脸付刷卡付条码付转账服务商模式,微信分账,微信合单支付、支持多种支付类型多支付账户，支付与业务完全剥离，简单几行代码即可实现支付，简单快速完成支付模块的开发，可轻松嵌入到任何系统里 目前仅是一个开发工具包（即SDK），只提供简单Web实现，建议使用maven或gradle引用本项目即可使用本SDK提供的各种支付相关的功能
pinyin-pro
中文转拼音、拼音音调、拼音声母、拼音韵母、多音字拼音、姓氏拼音、拼音匹配
pipiname
根据三才五格和古诗文给宝宝起名
protools
历经开发周期两年，并且应用过千万级别项目的工具箱
pyfreebilling
Freeswitch GUI wholesale application - GPL v3 -
r_in_action
机器学习实战＋统计建模＋ggplot2画图
retter
A collection of hash functions, ciphers, tools, libraries, and materials related to cryptography & security. :closed_lock_with_key:
shop
基于Spring-boot和bootstrap搭建的商城系统
spider
使用java+httpclient+httpcleaner，多线程、分布式爬去电商网站商品信息，数据存储在hbase上，并使用solr对商品建立索引，使用redis队列存储一个共享的url仓库；使用zookeeper对爬虫节点生命周期进行监视等。
storm-starter
Learn to use Storm!
tcp-ip-protocal
tcp/ip协议栈
terminal-changes-prediction
基于某城市移动终端用户的运营商数据预测未来三月内用户是否会终端变迁(用户从当前使用的手机品牌更换为其他手机品牌)。应用xgboost算法和随机森林算法组合成多学习器预测模型。
the-art-of-programming-by-july
本项目曾冲到全球第一，干货集锦见本页面最底部，另完整精致的纸质版《编程之法：面试和算法心得》已在京东/当当上销售！
tianyancha
scrapy 爬取天眼查网站的 公司注册信息
ua-device
userAgent解析库
wechat-app-mall
微信小程序商城，微信小程序微店
word_cloud
A little word cloud generator in Python
youpbx
A great GUI manager for FreeSwitch
zhihu_bigdata
使用scrapy和pandas完成对知乎300w用户的数据分析。首先使用scrapy爬取知乎网的300w，用户资料，最后使用pandas对数据进行过滤，找出想要的知乎大牛，并用图表的形式可视化。
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