ozturkc

apa6-turkish-latex-template

apa6 Türkçe Latex Döküman Taslağı - TUBİTAK Proje Yarışmasına Kullanılmıştır.

Diebold_BondYield

Recreation of Diebold and Li: Forecasting the term structure of government bond yields in python.

Django-Kitap-Satis

Django-Kitap-Satis2

dlaicourse

Notebooks for learning deep learning

eys2019

Machine-Learning

Machine-Learning-with-Python

Python code for common Machine Learning Algorithms

Otel-Rezervasyon-Sistemi

Personel-Sistemi

Java based desktop application.

ozturkc/apa6-turkish-latex-template

apa6 Türkçe Latex Döküman Taslağı - TUBİTAK Proje Yarışmasına Kullanılmıştır.

ozturkc/Diebold_BondYield

Recreation of Diebold and Li: Forecasting the term structure of government bond yields in python.

ozturkc/Django-Kitap-Satis

ozturkc/Django-Kitap-Satis2

ozturkc/dlaicourse

Notebooks for learning deep learning

ozturkc/eys2019

ozturkc/Machine-Learning

ozturkc/Machine-Learning-with-Python

Python code for common Machine Learning Algorithms

ozturkc/Otel-Rezervasyon-Sistemi

ozturkc/Personel-Sistemi

Java based desktop application.

ozturkc/Predictive_Maintenance_w_LSTM

Predictive_Maintenance_of_AircraftMotorHealth_with_LSTM_Method

ozturkc/r

R Uygulamalı Ekonometri

ozturkc/Sifirdan-Ileri-Seviyeye-Python-Programlama

Udemy üzerindeki Python kurslarında kullanılan materyaller

ozturkc/Stock-price-prediction-using-GAN

In this project, we will compare two algorithms for stock prediction. First, we will utilize the Long Short Term Memory(LSTM) network to do the Stock Market Prediction. LSTM is a powerful method that is capable of learning order dependence in sequence prediction problems. Furthermore, we will utilize Generative Adversarial Network(GAN) to make the prediction. LSTM will be used as a generator, and CNN as a discriminator. In addition, Natural Language Processing(NLP) will also be used in this project to analyze the influence of News on stock prices.

ozturkc/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.

ozturkc/tasarim-desenleri-turkce-kaynak

Türkçe kaynağa destek olması amacıyla oluşturulmuş bir kaynaktır. Konu anlatımının yanı sıra C#, Java, Go, Python, Kotlin ve TypeScript gibi birçok dilde tasarım desenlerinin uygulamasını içermektedir.

ozturkc/yield-curve-forecasting

This repository provides the implementation of a handful of forecasting methods in yield curve modelling.

ozturkc/Yield_Curve_Forecasting

First commit.