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vechkar's Projects

cleanarchitecture icon cleanarchitecture

Clean Architecture Solution Template: A starting point for Clean Architecture with ASP.NET Core

design_patterns_in_csharp icon design_patterns_in_csharp

In this repository I am doing some exercises and examples about the GOF design patterns in C# 7, so it's pretty much updated.

eshoponcontainers icon eshoponcontainers

Cross-platform .NET sample microservices and container based application that runs on Linux Windows and macOS. Powered by .NET Core 3.0, Docker Containers and Azure Kubernetes Services. Supports Visual Studio, VS for Mac and CLI based environments with Docker CLI, dotnet CLI, VS Code or any other code editor.

eshoponweb icon eshoponweb

Sample ASP.NET Core 2.0 reference application, powered by Microsoft, demonstrating a layered application architecture with monolithic deployment model. Download 130+ page eBook PDF from docs folder.

odata.net icon odata.net

ODataLib: Open Data Protocol - .NET/Silverlight/WP8.1 Libraries and Frameworks

principles-of-email-design icon principles-of-email-design

A repository of coding resources for anyone first dipping their toes into the waters of HTML email design. Godspeed.

reactinterface2 icon reactinterface2

Repository for the second version of my React Interface course on LinkedIn Learning and Lynda.com

serverless-microservices-reference-architecture icon serverless-microservices-reference-architecture

This reference architecture walks you through the decision-making process involved in designing, developing, and delivering a serverless application using a microservices architecture through hands-on instructions for configuring and deploying all of the architecture's components along the way. The goal is to provide practical hands-on experience in working with several Azure services and the technologies that effectively use them in a cohesive and unified way to build a serverless-based microservices architecture.

signalrchat icon signalrchat

Simple AngularJS that uses SignalR to implement a Chatroom on localhost

stockpredictionai icon 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.

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