LinqiChen0821

LinqiChen0821's Stars

• T12z/TCNopen

  (fork of SF:) TCNOpen - Components for IEC61375 standardised communication

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• PradeepThapa/nsl_kdd_classification

  Cyber-attack classification in the network traffic database using NSL-KDD dataset

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• PythonJulia/NSL-KDD-Data-Analysis

  NSL-KDD (for network-based intrusion detection systems (IDS)) is a dataset suggested to solve some of the inherent problems of the parent KDD'99 dataset. This IDS basically helps to determine security of systems and alarming when intrusion is noticed or detected. Choosing NSL-KDD provides insightful analysis using various machine learning algorithms for intrusion detection. Myself expecting to explore intuitive insights of intrusion detection and work on various machine learning algorithms that is reasonable to understand future instance of attacks and its types.

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• Youssef-AK/NSL-KDDCup99

  Work with NSL-KDD to reach best accuracy

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• yaseng/iot-security-wiki

  IOT security wiki

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• cxmirene/KDDCUP99-Detection

  使用贝叶斯、神经网络、KNN进行入侵检测（KDD-CUP99）

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• f/awesome-chatgpt-prompts

  This repo includes ChatGPT prompt curation to use ChatGPT better.

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• ggulgun/NIDS-Intrusion-Detection

  Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

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• fengdu78/lihang-code

  《统计学习方法》的代码实现

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• ylfeng250/KDD99CupDataSet-SVM

  clean data ,feature selection , svm based kdd99

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• wesm/pydata-book

  Materials and IPython notebooks for "Python for Data Analysis" by Wes McKinney, published by O'Reilly Media

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• ubeyu/tcnopen-trdp-extension

  个人开发，基于实验室校企合作项目，在tcnopen-trdp-trunk开源项目的基础上，扩展了一些列车通信网络应用层通信的代码，并移植在了树莓派4B集群上，构成了简单列车通信网络仿真平台，开源在这里供大家学习交流。

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• nndl/nndl.github.io

  《神经网络与深度学习》 邱锡鹏著 Neural Network and Deep Learning

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• iamseancheney/python_for_data_analysis_2nd_chinese_version

  《利用Python进行数据分析·第2版》

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