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algorithm011-class02

alibabacloud-redis-training-demo

anytext

bigdatatrain

canal

阿里巴巴 MySQL binlog 增量订阅&消费组件

clickhouse

ClickHouse is a free analytics DBMS for big data

coding-interview-university

A complete computer science study plan to become a software engineer.

datasets

🤗 The largest hub of ready-to-use datasets for ML models with fast, easy-to-use and efficient data manipulation tools

ddia

《设计数据密集型应用》总结思维导图

docs

EasyWeChat documentation.

drrg

Deep relational reasoning graph network for arbitrary shape text detection; Accepted by CVPR 2020 (Oral). http://arxiv.org/abs/2003.07493

dwsurvey

DwSurvey is an open source web survey system. 最好用问卷调查系统、表单系统。

easypusher

免费组件：简单、高效、稳定、免费的一款标准RTSP/RTP协议直播推送库，支持将H.264/H.265/G.711/G.726/AAC等音视频数据推送到RTSP流媒体服务器（例如EasyDarwin）进行低延时直播或者视频通信，支持Windows、Linux、ARM、Android、iOS等平台，EasyPusher配套EasyDarwin流媒体服务器、EasyPlayer RTSP播放器适用于特殊行业的低延时应急指挥需求！ Android迁移到了https://github.com/EasyDarwin/EasyPusher-Android , iOS迁移到了https://github.com/EasyDarwin/EasyPusher-iOS

facebook_crawler

ferry

本系统是集工单统计、任务钩子、权限管理、灵活配置流程与模版等等于一身的开源工单系统，当然也可以称之为工作流引擎。 致力于减少跨部门之间的沟通，自动任务的执行，提升工作效率与工作质量，减少不必要的工作量与人为出错率。

go

The Go programming language

grok-1

Grok open release

hbase_syllabus

HBase基本API操作

hft

real high-frequency-trading system based on c++

hmily

Distributed transaction solutions

java-000

javacoursecodes

JavaCourse

jksjspring

justauth

:100: 史上最全的整合第三方登录的开源库。目前已支持Github、Gitee、微博、钉钉、百度、Coding、腾讯云开发者平台、OSChina、支付宝、QQ、微信、淘宝、Google、Facebook、抖音、领英、小米、微软、今日头条、Teambition、StackOverflow、Pinterest、人人、华为、企业微信、酷家乐、Gitlab、美团、饿了么和推特等第三方平台的授权登录。 Login, so easy!

langchain

⚡ Building applications with LLMs through composability ⚡

leveldb

LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values.

lightseq

LightSeq: A High Performance Library for Sequence Processing and Generation

llm-quickstart

大语言模型快速入门（理论学习与微调实战）

mias

Indexes text with math in Lucene/Solr-based full-text search engines

ml-nlp

此项目是机器学习(Machine Learning)、深度学习(Deep Learning)、NLP面试中常考到的知识点和代码实现，也是作为一个算法工程师必会的理论基础知识。