DataGeeek

dataviz, ggplot2, tidymodels, tidyquant, tidyverse, VLOOKUP, waffle

Modeling with Interaction Terms, and Waffle Chart for Comparing: Immigration Flow to the West

Published by

Selcuk Disci

on

May 31, 2022

There has been a massive debate about the refugee crisis in Turkey for a long time. Turkish people blame immigrants (mostly from Syria) for the worsening economy, and they believe that the immigrants are in wealthy conditions while they themselves suffer from bad economic conditions. I want to check the…
Continue reading →: Modeling with Interaction Terms, and Waffle Chart for Comparing: Immigration Flow to the West
Bayesian estimation, jags, mcmc, rjags, simulation

Military Expenditure Estimation with RJAGS Simulation

Published by

Selcuk Disci

on

April 29, 2022

The side effect of the ongoing Russian occupation was that it stimulated countries’ intentions to increase their military budgets. Last month following the invasion, Germany announced a budget of 100 billion € for the restructuring of the army and announced that it would spend %2 of its GDP every year.…
Continue reading →: Military Expenditure Estimation with RJAGS Simulation
data masks, fable, ggplot2, ggplotly, neural network, neural network autoregression, NNETAR, plotly, tidyverse, time series forecasting

Nuclear Threat Projection with Neural Network Time Series Forecasting

Published by

Selcuk Disci

on

March 28, 2022

Unfortunately, we have been through tough times recently as going on Russian invasion in Ukraine. As Putin stacked to the corner via sanctions and lost in the field, he has been getting to be more dangerous. He has even threatened to use nuclear weapons if necessary. Because of the nuclear…
Continue reading →: Nuclear Threat Projection with Neural Network Time Series Forecasting
adabag, bagging, boosting, caret, ggplot2, kappa, plotly, simulation, time series forecasting, treemap

Meta-Learning: Boosting and Bagging for Time Series Forecasting

Published by

Selcuk Disci

on

February 28, 2022

I am always struggled to model the changes in gasoline prices as a categorical variable, especially in a small amount of time-series data. The answer to improving the performance of modeling such a dataset can be to combine more than one model. This method of combining and aggregating the predictions…
Continue reading →: Meta-Learning: Boosting and Bagging for Time Series Forecasting

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I’m Selcuk Disci

The DataGeeek focuses on machine learning, deep learning, and Generative AI in data science using financial data for educational and informational purposes.

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Modeling with Interaction Terms, and Waffle Chart for Comparing: Immigration Flow to the West

Military Expenditure Estimation with RJAGS Simulation

Nuclear Threat Projection with Neural Network Time Series Forecasting

Meta-Learning: Boosting and Bagging for Time Series Forecasting

I’m Selcuk Disci

Let’s connect

Join the fun!