cycleliu

cycleliu's Stars

• go-admin-team/go-admin

  基于Gin + Vue + Element UI & Arco Design & Ant Design 的前后端分离权限管理系统脚手架（包含了：多租户的支持，基础用户管理功能，jwt鉴权，代码生成器，RBAC资源控制，表单构建，定时任务等）3分钟构建自己的中后台项目；项目文档》：https://www.go-admin.pro V2 Demo： https://vue2.go-admin.dev V3 Demo： https://vue3.go-admin.dev Antd 订阅版：https://antd.go-admin.pro

  Language:Go11.2k2.3k

• donnemartin/system-design-primer

  Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

  Language:Python265k45k

• golang/go

  The Go programming language

  Language:Go122k17.4k

• github/dev

  Press the . key on any repo

  1.2k2.9k

• ory/dockertest

  Write better integration tests! Dockertest helps you boot up ephermal docker images for your Go tests with minimal work.

  Language:Go4k240

• avelino/awesome-go

  A curated list of awesome Go frameworks, libraries and software

  Language:Go126k11.7k

• Snailclimb/guide-rpc-framework

  A custom RPC framework implemented by Netty+Kyro+Zookeeper.（一款基于 Netty+Kyro+Zookeeper 实现的自定义 RPC 框架-附详细实现过程和相关教程。）

  Language:Java3.8k2k

• naraquev/Private-AI

  All exercises from private AI Facebook Scholarship

  Language:Jupyter Notebook132

• SAP-samples/machine-learning-diff-private-federated-learning

  Simulate a federated setting and run differentially private federated learning.

  Language:Python35092

• gwynwilkinson/iris-pysyft

  Iris Dataset - Federated Learning implementation using PySyft

  Language:Jupyter Notebook4

• saranshmanu/Federated-Learning

  Federated Learning is a distributed machine learning approach which enables model training on a large corpus of decentralised data. The repository tutorial for using PySyft for distributed training of Machine Learning model.

  Language:HTML4222

• bipraneelroy/Intrusion-Detection-over-IoT-network

  Deep Learning based model for detecting intrusions in IoT traffic

  Language:Jupyter Notebook1

• FlamingJay/Time-related-Intrusion-Detection-Model-based-on-Recurrent-Neural-Network

  Here, we use RNN to deal with the network intrusion problem. The UNSW-NB15 dataset is used.

  Language:Python6519

• devendra416/Network-Intrusion-Detection-system-using-Deep-learning

  Language:Jupyter Notebook64

• TGyAlDeen/IDS-UNSW-NB15

  IoT intrusion Detection Model based on neural network and random forests

  Language:Jupyter Notebook4419

• Faridbg/CNN_UNSW-NB15

  DISEÑO Y EVALUACIÓN DE REDES NEURONALES CONVOLUCIONALES PARA UN SISTEMA DE DETECCIÓN DE INTRUSIONES

  Language:Jupyter Notebook131

• anantsh-dev/Federated-Learning

  Implementation of a Federated Learning based CNN model

  Language:Python141

• munirKarsli/Network-Intrusion-Detection-With-Deep-Learning-On-Nsl-Kdd-Dataset

  Language:Jupyter Notebook2113

• Jumabek/net_intrusion_detection

  Network intrusion detection with Machine Learning (Deep Learning) experiment : 1d-cnn, softmax, neural networks, convolution

  Language:Jupyter Notebook3514

• tmendonca28/DLNID

  The code for my MSc. in Applied Cyber Security research project titled "Machine Learning for Network Intrusion Detection". Explored the use of RNN and MLP for network intrusion detection and classification. Used PyTorch.

  Language:Jupyter Notebook6

• zhanghad/Federated_Learning

  A federated learning project on Android platform. The project was initiated by the College of Intelligence and Computing, Tianjin University.

  82

• CodingDocs/awesome-java

  Collection of awesome Java project on Github(非常棒的 Java 开源项目集合).

  8.8k1.6k

• yilifzf/BDCI_Car_2018

  BDCI 2018 汽车行业用户观点主题及情感识别 决赛一等奖方案

  Language:Python427158

• neoremind/2018-polar-race

  1st AliCloud Database Performance Competition in 2018 - Java rank No.1 source code 阿里云2018年第一届PolarDB数据库性能大赛Java排名第一源码

  Language:Java19866

• ityouknow/spring-boot-examples

  about learning Spring Boot via examples. Spring Boot 教程、技术栈示例代码，快速简单上手教程。

  Language:Java30.1k12.3k

• dyc87112/SpringBoot-Learning

  《Spring Boot基础教程》，2.x版本持续连载中！点击下方链接直达教程目录！

  Language:Java15.7k4.9k

• CharlieDDDD/KDD-Cup-99-CNN-PyTorch

  This is a classification model with five classes (normal, DOS, R2L, U2R,PROBING). Ignore the content features of TCP connection ( columns 10-22 of KDD Cup 99 dataset) when training the model to adapt the project that a kdd99 feature extractor

  Language:Python286

• vivekkhimani/federated_learning_pysyft

  A simple federated learning implementation on MNIST dataset using PySyft. Main goal of the project was to get used to the PySyft federated learning functionality instead of using traditional PyTorch features.

  Language:Python12

• jaywcjlove/mysql-tutorial

  MySQL入门教程（MySQL tutorial book）

  4.2k802

• labuladong/fucking-algorithm

  刷算法全靠套路，认准 labuladong 就够了！English version supported! Crack LeetCode, not only how, but also why.

  Language:Markdown124k23.1k