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An example attention network with simple dataset.
A curated list of awesome Machine Learning frameworks, libraries and software.
一个PyTorch搭建CNN的中文基础教程
Deep Learning and Rare Event Prediction
检测恶意 URL and Request (Bi-LSTM、Bi-LSTM + CNN、CNN + Bi-LSTM、CNN + Bi-LSTM + CNN)
Easy differential privacy in R
Pytorch implementation of DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks
Defending graph neural networks against adversarial attacks (NeurIPS 2020)
Multi-variate time series forecasting using ML algorithms
Official code for the INFOCOM 2020 paper "Guardian: Evaluating Trust in Online Social Networks with Graph Convolutional Networks."
Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.
A deep learning project: RNN and its implementation in anomoly detection
The continuing increase of Internet of Things (IoT) based networks have increased the need for Computer networks intrusion detection systems (IDSs). Over the last few years, IDSs for IoT networks have been increasing reliant on machine learning (ML) techniques, algorithms, and models as traditional cybersecurity approaches become less viable for IoT. IDSs that have developed and implemented using machine learning approaches are effective, and accurate in detecting networks attacks with high-performance capabilities. However, the acceptability and trust of these systems may have been hindered due to many of the ML implementations being ‘black boxes’ where human interpretability, transparency, explainability, and logic in prediction outputs is significantly unavailable. The UNSW-NB15 is an IoT-based network traffic data set with classifying normal activities and malicious attack behaviors. Using this dataset, three ML classifiers: Decision Trees, Multi-Layer Perceptrons, and XGBoost, were trained. The ML classifiers and corresponding algorithm for developing a network forensic system based on network flow identifiers and features that can track suspicious activities of botnets proved to be very high-performing based on model performance accuracies. Thereafter, established Explainable AI (XAI) techniques using Scikit-Learn, LIME, ELI5, and SHAP libraries allowed for visualizations of the decision-making frameworks for the three classifiers to increase explainability in classification prediction. The results determined XAI is both feasible and viable as cybersecurity experts and professionals have much to gain with the implementation of traditional ML systems paired with Explainable AI (XAI) techniques.
用于存放学习笔记
Compare how ANNs, RNNs, LSTMs, and LSTMs with attention perform on time-series analysis
Library for training machine learning models with privacy for training data
Differentially private synthetic data
RAPPOR: Privacy-Preserving Reporting Algorithms
Privacy-preserving generative deep neural networks support clinical data sharing
Stacked Bidirectional and Unidirectional LSTM Recurrent Neural Network
My study notes on time series. Will keep updating.
A study journal of time series analysis: ARIMA algorithm. With market sales dataset practice.
Traffic Graph Convolutional Recurrent Neural Network
Source code of paper "TrustGuard: GNN-based Robust and Explainable Trust Evaluation with Dynamicity Support"
尝试
A declarative, efficient, and flexible JavaScript library for building user interfaces.
🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. 📊📈🎉
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google ❤️ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.