LIYAO9336

LIYAO9336's Stars

• kdn251/interviews

  Everything you need to know to get the job.

  Language:Java63.3k2.6k5312.9k

• xkcoding/spring-boot-demo

  🚀一个用来深入学习并实战 Spring Boot 的项目。

  Language:Java32.9k1k16510.8k

• qishibo/AnotherRedisDesktopManager

  🚀🚀🚀A faster, better and more stable Redis desktop manager [GUI client], compatible with Linux, Windows, Mac.

  Language:JavaScript30.2k2609972.5k

• 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

  Language:Java28.2k864478.1k

• alibaba/spring-cloud-alibaba

  Spring Cloud Alibaba provides a one-stop solution for application development for the distributed solutions of Alibaba middleware.

  Language:Java27.8k9742.4k8.3k

• lenve/vhr

  微人事是一个前后端分离的人力资源管理系统，项目采用SpringBoot+Vue开发。

  Language:Java27.3k87825310.3k

• qiurunze123/miaosha

  ⭐⭐⭐⭐秒杀系统设计与实现.互联网工程师进阶与分析🙋🐓

  Language:Java26.2k40806.6k

• hollischuang/toBeTopJavaer

  To Be Top Javaer - Java工程师成神之路

  Language:Java25.3k9121275.5k

• dianping/cat

  CAT 作为服务端项目基础组件，提供了 Java, C/C++, Node.js, Python, Go 等多语言客户端，已经在美团点评的基础架构中间件框架（MVC框架，RPC框架，数据库框架，缓存框架等，消息队列，配置系统等）深度集成，为美团点评各业务线提供系统丰富的性能指标、健康状况、实时告警等。

  Language:Java18.6k1.1k1.3k5.4k

• macrozheng/mall-learning

  mall学习教程，架构、业务、技术要点全方位解析。mall项目（60k+star）是一套电商系统，使用现阶段主流技术实现。涵盖了SpringBoot、MyBatis、Elasticsearch、RabbitMQ、Redis、MongoDB、Mysql等技术，采用Docker容器化部署。

  Language:Java12.9k342898.3k

• frank-lam/fullstack-tutorial

  🚀 fullstack tutorial 2022，后台技术栈/架构师之路/全栈开发社区，春招/秋招/校招/面试

  Language:Java11.5k381392.4k

• lihengming/spring-boot-api-project-seed

  :seedling::rocket:一个基于Spring Boot & MyBatis的种子项目，用于快速构建中小型API、RESTful API项目~

  Language:Java9.6k4441963.8k

• zhoutaoo/SpringCloud

  基于SpringCloud2.1的微服务开发脚手架，整合了spring-security-oauth2、nacos、feign、sentinel、springcloud-gateway等。服务治理方面引入elasticsearch、skywalking、springboot-admin、zipkin等，让项目开发快速进入业务开发，而不需过多时间花费在架构搭建上。持续更新中

  Language:Java8.7k3551283.9k

• scikit-learn-contrib/imbalanced-learn

  A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning

  Language:Python6.8k1425941.3k

• DocsHome/microservices

  Microservices from Design to Deployment 中文版 《微服务：从设计到部署》

  5.1k26271k

• yizhiwazi/springboot-socks

  SpringBoot 基础教程 | 从入门到上瘾 | 基于2.0.0.M5制作

  Language:Java2.6k130151.4k

• geekidea/spring-boot-plus

  :fire: Spring-Boot-Plus is an easy-to-use, high-speed, high-efficient,feature-rich, open source spring boot scaffolding. :rocket:

  Language:Java2.5k9664721

• spring-projects/spring-integration-samples

  You are looking for examples, code snippets, sample applications for Spring Integration? This is the place.

  Language:Java2.3k246922.6k

• scikit-multiflow/scikit-multiflow

  A machine learning package for streaming data in Python. The other ancestor of River.

  Language:Python75627190182

• ZHENFENG13/concurrent-programming

  :cactus:《实战java高并发程序设计》源码整理

  Language:Java625323245

• Licoy/watchdog-framework

  :beers: 基于SpringBoot+Shiro+Mybatis等开发的轻量级管理系统快速开发脚手架

  Language:Java439366172

• Motianshi/distribute-tool

  分布式工具

  Language:Java20891117

• binli826/LSTM-Autoencoders

  Anomaly detection for streaming data using autoencoders

  Language:Python1859646

• marquisXuan/netty

  博文源码

  Language:Java17213393

• TyCoding/spring-learn

  :art: :tada: :tada: 这里有丰富的Spring框架学习案例

  Language:JavaScript1415058

• Licoy/watchdog-framework-web

  :beers: 【新版计划中】watchdog-framework的Web前端项目，基于Vue+iView-Admin+Vue-Router+Vuex开发

  Language:Vue12716778

• elena-sharova/IsolationForest

  testing scikit-learn Isolation Forest

  Language:Jupyter Notebook746172

• JJRyan0/outlier-detection-algorithm-isolation-forests

  BNP Paribas Kaggle Data Set Data source: https://www.kaggle.com/c/bnp-paribas-cardif-claims-management Outlier Detection- Ensemble unsupervised learning method - Isolation Forest The isolation algorithm is an unsupervised machine learning method used to detect abnormal anomalies in data such as outliers. This is once again a randomized & recursive partition of the training data in a tree structure. The number of sub samples and tree size is specified and tuned appropriately. The distance to the outlier is averaged calculating an anomaly detection score: 1 = outlier 0 = close to zero are normal data.

  Language:Python16205

• tharindurb/iNNE

  Language:Java9204

• kpriyanshu256/AnomalyDetection

  Using Isolation Forest

  Language:Jupyter Notebook1100