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emrecanduran/README.md

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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  1. End-to-End-Azure-ML-Regression-Deployment End-to-End-Azure-ML-Regression-Deployment Public

    This repository contains code and resources for deploying a machine learning regression model using Azure App Service for a real estate house price prediction.

    Python

  2. SAS-Enterprise-Miner-Wonderful-Wines-Of-The-World-Predictive-Modeling SAS-Enterprise-Miner-Wonderful-Wines-Of-The-World-Predictive-Modeling Public

    In this project, it is applied Neural Networks and Decision Tree predictive models in SAS Enterprise Miner, compared the models and choose the best model to predict target column in unseen data.

  3. Databricks-Big-Data-Reordered-Prediction Databricks-Big-Data-Reordered-Prediction Public

    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-squa…

    Jupyter Notebook

  4. Relational-Database-Fictitious-Business Relational-Database-Fictitious-Business Public

    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 f…

  5. Top-250-French-Movies-EDA-Sentimental-Analysis Top-250-French-Movies-EDA-Sentimental-Analysis Public

    In this project, it is applied EDA, WordCloud visualization and Sentimental Analysis to understand overall mood of the movies by audience.

    Jupyter Notebook

  6. Marketing-Campaign-Response-Prediction Marketing-Campaign-Response-Prediction Public

    Develop a model to predict which retail customers will respond to a marketing campaign. Logistic Regression shows the best performance.

    Jupyter Notebook