Yjl_cc's Projects
Config files for my GitHub profile.
一个记录成长的blog!
This project includes the simulation for adaptive merging of video processing services.
A project that is used to analyze multiple machine learning classifiers for DDoS detection from botnets and finalize the best classifier.(Research Project)
Anomaly detection related books, papers, videos, and toolboxes
AnomalyDAE (ICASSP2020)
A curated list of awesome anomaly detection resources
A program to find the best arrangement of resources in the Colonel Blotto Game by genetic algorithm
Topological botnet detection datasets and graph neural network applications
2021年最新整理,5000道秋招/提前批/春招/常用面试题(含答案),包括leetcode,校招笔试题,面试题,算法题,语法题。持续更新中
A project using CloudSim to simulate cloud scheduling and resource provisioning for video transcoding
CloudSimPy: Datacenter job scheduling simulation framework
[TPDS'21] COSCO: Container Orchestration using Co-Simulation and Gradient Based Optimization for Fog Computing Environments
吴恩达老师的机器学习课程个人笔记
后端架构师技术图谱
:books: 技术面试必备基础知识、Leetcode、计算机操作系统、计算机网络、系统设计、Java、Python、C++
My attempt at reproducing the paper Deep Autoencoding Gaussian Mixture Model for Unsupervised Anomaly Detection
DAGMM Tensorflow implementation
DDos-Attack Is A Python script online Attack
In this Project, A simulation of a network traffic is created to track and capture the patterns from any type of DDoS attacks with the help of SVM model. By using rule detection and SVM model together, the results deliver the details of the attack. This helps in improving the detection rate of the DDoS attacks from flooding or crashing the user’ services.
Crowdfunding defense: ddos detection based on blockchain by hyperledger fabric
early detection and mitigation of DDos using centralized SDN controller POX
DDoS attack analysis using Machine Learning
Open-source benchmark suite for cloud microservices
Repository of the paper "A Systematic Evaluation of Deep Anomaly Detection Methods for Time Series".
深度学习500问,以问答形式对常用的概率知识、线性代数、机器学习、深度学习、计算机视觉等热点问题进行阐述,以帮助自己及有需要的读者。 全书分为15个章节,近20万字。由于水平有限,书中不妥之处恳请广大读者批评指正。 未完待续............ 如有意合作,联系[email protected] 版权所有,违权必究 Tan 2018.06
开发者边车,github打不开,github加速,git clone加速,git release下载加速,stackoverflow加速
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为TensorFlow 2.0实现,项目已得到李沐老师的认可
[TMC'20] Deep Learning based Scheduler for Stochastic Fog-Cloud computing environments