Arthur Stankevich's repositories
remove-background-telegram-bot
Telegram Bot to Remove Image Background
a-stankevich.github.io
Developer's profile
aiquestions
Questions that AI is supposedly unable to answer
angularjs-webpack
A complete, yet simple, starter for Angular using webpack
CodeceptJS
Supercharged End 2 End Testing Framework for NodeJS
codeceptjs-ui
Web UI for CodeceptJS
DevExpressSchedulerIssue
.NET, ASP.NET MVC, MVC Scheduler
docker-dotnet-example
Demonstrates configuration of Docker and .NET Core for a development workflow
EntityFramework.Functions
EntityFramework.Functions library implements Entity Framework code first support for stored procedures (with single result type, multiple result types, output parameter), table-valued functions (returning entity type, complex type), scalar-valued functions (composable, non-composable), aggregate functions, built-in functions, niladic functions, and model defined functions.
GeoEstimation
This repository contains all necessary meta information, results and source files to reproduce the results in the publication Eric Müller-Budack, Kader Pustu-Iren, Ralph Ewerth: "Geolocation Estimation of Photos using a Hierarchical Model and Scene Classification", In: European Conference on Computer Vision (ECCV), Munich, 2018.
LinqKit_Issue59
Code to reproduce https://github.com/scottksmith95/LINQKit/issues/59
localtunnel.net
.NET implementation of a tunnel client for localtunnel.me.
markdown-scanner
Application for scanning markdown documentation and generating test cases for APIs.
ng-input-currency
input formatter as currency with Angular
ng-sortable
AngularJS Library for Drag and Drop, supports Sortable and Draggable. No JQuery/JQuery UI used. Supports Touch devices.
Owin.Compression
Compression (Deflate / GZip) module for Microsoft OWIN Selfhost filesystem pipeline.
SocksSharp
SocksSharp provides support for Socks4/4a/5 proxy servers to HttpClient
SshAgentLib
.NET library creating ssh agent and client applications (works with both PuTTY/Pageant and OpenSSH)
stockpredictionai
In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.