Furkan Alaybeg

Recurrent Neural Network (RNN), LSTM (Long Short-Time Memory), Bitcoin, Google Trends, Prediction, Deep Learning

The project was written in C# Asp.Net MVC environment using N-Tier Architecture and Web API, Entity Framework, Code First, Linq, Jquery, Bootstrap technologies.

This repository includes supervised and unsupervised machine learning methods which are used to detect anomalies on network datasets. Decision Tree, Random Forest, Gradient Boost Tree, Naive Bayes, and Logistic Regression were used for supervised learning. K-Means was used for unsupervised learning.

Object Oriented Programming (OOP) sample projects were written in C# language.

In this repository was written a simple cross-platform e-commerce mobile project. Web API was used for CRUD operations and Identity Server for login authentication.

In this repository a sample project was written using SignalR library. The project consists of chat application and notification screens.