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Hi there 👋, I'm Emrecan

I'm currently doing my master's degree in Data Science. I really enjoy learning about Machine Learning and how it's used in different areas. Even though I do not have professional experience yet, I continue to learn and discover the unlimited applications of data science.

The tools I use:

  • Python 🐍: Data analysis, manipulation, visualization and modeling.
  • MySQL 🗄️: Data retrieval, and manipulation.
  • Databricks 💻: Skilled in utilizing Databricks for big data analytics and machine learning applications.
  • SAS 📊: Familiar with SAS for statistical analysis, data management, reporting purposes and modeling.
  • Azure Web App ☁️: Gaining experience by deploying machine learning models as web applications on the Azure platform.

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emrecanduran 's Projects

bike-rental-regression-models icon bike-rental-regression-models

This repository contains code for a bike rental prediction models including Random Forest, XGBoost, GradientBoosting, and Lasso Regression.

databricks-big-data-reordered-prediction icon databricks-big-data-reordered-prediction

This repository contains code and resources for performing EDA and, predictive modeling on a large-scale e-commerce dataset using PySpark and SQL. Additionally, Hypothesis testing by using Chi-square is applied to features.

google-analytics-4-api-analyzing-my-blog-page icon google-analytics-4-api-analyzing-my-blog-page

In this repository, I performed an analysis of my blog page 6 months data from a Google Analytics 4 (GA4) account using Google Cloud services within a Jupyter notebook. The aim of this project is to leverage my knowledge of GA4 in conjunction with my proficiency in Jupyter notebooks to conduct an analysis.

relational-database-fictitious-business icon relational-database-fictitious-business

Create a relational database using MySQL for a fictional small business that offers products or services, allowing customers to rate their experience, while keeping in mind the three normal forms for database design.

rfm-analysis-wonderful-wines-of-the-world icon rfm-analysis-wonderful-wines-of-the-world

In this project, I utilized the RFM Model on the WonderfulWines dataset. As a noteworthy enhancement, I employed a log transformation to achieve greater data symmetry, which ultimately resulted in more accurate outcomes.

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