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Hamza Guner Portfolio

About Me

I am a Management Information Systems (MIS) student specializing in Data Science. I am passionate about transforming data into actionable insights and solving real-world problems through innovative solutions. My academic background has equipped me with strong analytical and programming skills.

Interests: Machine Learning, Natural Language Processing, and Data Visualization. My goal is to contribute to impactful projects and enhance my expertise in Data Science.

Education

Projects

Climate Migration Risk Analysis and Forecasting in Europe

The Climate Migration Project focuses on understanding the social impacts of climate change and providing solutions. I develop knowledge and tools to support people to adapt to new living spaces.

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Earthquake Tweet Analysis

Developed an algorithm to classify tweets during earthquakes to identify genuine help requests and reduce spam.

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Energy Consumption Estimation

eveloped a machine learning model to predict energy consumption patterns for homes and businesses. Leveraged historical energy usage data to provide accurate forecasts and insights for efficient energy management.

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Online Shopping Site

This project implemented a phone class design using Object Oriented Programming (OOP) principles. It aims to learn basic OOP concepts such as encapsulation, abstraction, inheritance and polymorphism in practice.

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Titanic Survival Prediction Using Machine Learning

Using machine learning techniques, this project analyzes Titanic passengers' survival probabilities based on demographic and travel data. Includes data preprocessing, visualization, and model building.

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My Personal Website

Created a responsive personal portfolio website to showcase my projects and blog posts. Developed using HTML, CSS, and hosted on GitHub Pages.

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Blog

Coming soon! Stay tuned for my insights on Data Science and technology trends.

Contact

Feel free to reach out to me.

Email: gunermuhammedhamza@gmail.com

Phone: +90 (537) 8221412

LinkedIn: Hamza Guner

GitHub: hamzaguner