Pinned Repositories
2.0.0
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wtospit's Repositories
wtospit/Angular-DD
Angular: Working with Derivative Data using RxJS
wtospit/Anomaly-Detection-using-Autoencoders
An Anomaly detection system built using autoencoders.
wtospit/basic-ng-testing-set
wtospit/beego
beego is an open-source, high-performance web framework for the Go programming language.
wtospit/BMW-YOLOv4-Inference-API-CPU
This is a repository for an nocode object detection inference API using the Yolov4 and Yolov3 Opencv.
wtospit/BMW-YOLOv4-Inference-API-GPU
This is a repository for an nocode object detection inference API using the Yolov3 and Yolov4 Darknet framework.
wtospit/Hacktoberfest-2018-First-Pull-Request
Add your Name to the README file and Submit your first Pull Request for Hacktoberfest 2018!
wtospit/hacktoberfest-firstPR
Making your first contribution
wtospit/Hacktoberfest2018
Welcome! I need some help making my website... Learn how in the README
wtospit/IoT-Network-Intrusion-Detection-and-Classification-using-Explainable-XAI-Machine-Learning
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.
wtospit/mt4-go-fork
Metratrader manager api on golang
wtospit/MT4API_ver3-fork
An MT4 manager API for the user management system with controllers in group, trades, orders and users
wtospit/MT4BridJAPI
wtospit/MT4JnaApi
rockfort
wtospit/MT4Lib
wtospit/mtmanapi-fork
go wrapper for mt4 manager api
wtospit/my-hello-world
Hacktoberfest First Project
wtospit/ngx-dropzone-wrapper
Angular wrapper library for Dropzone
wtospit/node-clean-architecture
Clean Architecture implementation written in NodeJS
wtospit/node-worker-threads-pool
Simple worker threads pool using node's worker_threads module.
wtospit/OrgChart.js
It's a simple and direct organization chart plugin. Anytime you want a tree-like chart, you can turn to OrgChart.
wtospit/pokerhand
wtospit/pool
🚌 A golang general network connection poolction pool
wtospit/popcat-echo
The server reproduction of https://popcat.click with improvement.
wtospit/progressive-web-cat
wtospit/reactjs-functions
wtospit/Robotframework-Database-Library
Database Library contains utilities meant for Robot Framework's usage. This can allow you to query your database after an action has been made to verify the results. This is compatible* with any Database API Specification 2.0 module.
wtospit/ssh2-sftp-client
a client for SSH2 SFTP
wtospit/typebox
JSON Schema Type Builder with Static Type Resolution for TypeScript
wtospit/watchdog